Reddit

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Home Experience team is responsible for one of the highest traffic pages on the platform: the Feed pages on the Reddit apps and website. Feeds are both a destination and entrypoint for almost all Reddit journeys, and we know a smooth, intuitive, and delightful experience is critical to Reddit’s success and appeal. You’ll be working with the immense scale of hundreds of millions of users to help them explore Reddit and provide them with excellent feeds on Reddit. What You’ll Do: - Work cross-functionally, collaborate and partner with product, design, and other engineering counterparts to build novel products and features that our users will love. - Work alongside a team of thoughtful, fast-moving, and motivated engineers. Contribute to standards that improve developer workflows, recommend best practices, and help mentor engineers on the team to grow their technical expertise. - Own the full development cycle for major projects: design, development, test, experimentation, analysis, and launch. You’ll be writing and reviewing code and design docs, giving feedback on product specs and mocks, and ensuring successful delivery of these key projects. - You will be a key driver in the planning, development, and implementation across Reddit’s backend service architecture in service of our native mobile and web clients as part of a full stack team. - Enable a culture of metrics led execution, with a focus on operational excellence and system observability. - Partner with leadership and cross-functional partners to develop the right roadmap that best achieves our product and engineering goals. Who You Might Be: - 6+ years of experience as a software engineer developing user-facing applications - Fluency working with product metrics, designing and analyzing experiments with exposure to tools like BigQuery, HEX, Firebase, etc. - Software development experience in one or more general purpose programming languages; e.g. Python, Go, Swift, Kotlin, Rust, C# - Experience leveraging GenAI tools to increase software engineering productivity. - Experience working with ML engineering teams and integrating ML solutions is a plus. - Strong organizational skills, the ability to breakdown and prioritize tasks for yourself and others while keeping projects on schedule. - BS degree in Computer Science, similar technical field of study, or equivalent practical experience. - Strong focus on user experience and usability. You are an undying advocate for the user, and you have a deep intuition for how people think and how they interact with software. Experience with social is a huge plus. - Entrepreneurial spirit. You must be self-directed, innovative, and biased towards action. You live to build new things and thrive in ambiguity. - Excellent communication skills. You must be able to collaborate with teams in a fully remote environment, and discuss complex topics with technical and non-technical audiences. Benefits: - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k with Employer Match - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $190,000 - $267,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We're looking for a Senior Client Account Manager to join our Global Strategic Accounts team. This team is a specialized group within Global Large Customer Sales that oversees Reddit’s most significant global advertising partners end-to end, by leading joint business planning, global strategy, and cross-regional execution. This person will closely collaborate with their Client Partner on campaign execution and optimizations to help agencies and advertisers achieve their marketing objectives on the fast-growing Reddit platform. This role is required to be based in person in San Francisco or New York. Responsibilities: - Collaborate closely with Client Partners to meet and exceed clients’ marketing goals - Lead and execute campaign launches from start to finish and deliver insightful optimizations to agency and client partners - Run end-to-end global account operations: revenue delivery, complex media strategy, multi-market optimizations, troubleshooting, and structured upsell on a global book - Turn campaign performance and tests across markets into global playbooks and measurement frameworks, feeding back into Product, Marketing Sciences, and Client Partners - Proactively manage and deepen relationships with existing advertising partners, both with agencies and directly with Global clients, to drive year-on-year Reddit revenue growth - Educate brands and media agencies, effectively communicate value proposition and best practices - Consult clients on their awareness and direct response objectives, and partner closely with Client Partners to craft thoughtful and creative media plans - Collaborate with Ad Ops to ensure effective campaign delivery and resolve any technical hurdles - Proactively seek and represent client needs and asks to cross-functional stakeholders - Shape Reddit’s native ads product roadmap, for mobile and in general, by aggregating and sharing client feedback and campaign metrics with cross-functional stakeholders - Proactively and continually identify areas of improvement - Mentor and train other team members. Required Qualifications: - 8+ years of experience in advertising sales and account management, global client experience is a plus - Strong understanding of customer marketing funnel and traditional marketing ecosystem - Comfortable with problems of diverse scope where analysis of data requires evaluation of identifiable factors. - Understanding of Digital measurement, tracking fundamentals and mobile measurement partners - Tenacious and entrepreneurial approach to working through product, process, and client challenges - Experience cultivating strong relationships with external partners - Exceptional communication and interpersonal skills - Ability to work in a fast-paced and unstructured work environment - High attention to detail - Proficiency in Excel preferred - BA / BS degree or equivalent work experience Benefits: - Comprehensive Health benefits - 401k Matching - Workspace benefits for your home office - Personal & Professional development funds - Family Planning Support - Flexible Vacation (please use them!) & Reddit Global Days Off - 4+ months paid Parental Leave - Paid Volunteer time off LI-NT1 #LI-onsite Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and will also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $135,100 - $189,200 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Team: Shopping at Reddit is one of the company's biggest bets. Shopping is core to Reddit's monetization strategy and Dynamic Product Ads (DPA) is one of our fastest-growing verticals. The Shopping product org has end-to-end ownership of how advertisers and Redditors interact with products and purchasing decisions. Our strategy is built on Reddit's unique strength - authentic, community-generated content. The Opportunity: The Product Catalog is the single source of truth for product data across paid and organic Shopping. It powers paid and organic shopping products and the Product Knowledge Graph (PKG). We're hiring a Product Manager to own Catalogs and Applied PKG end-to-end. The aspiration is to turn this asset into a platform that drives ROAS and powers product discovery across Reddit. This role sits at the intersection of advertiser tooling, product & content understanding and user experiences. You will partner deeply with the Catalogs engineering team, the Ads Content Understanding (ACU) team, and the Shopping product team across performance, formats and more. What You'll Do: - Cut advertiser onboarding friction and prepare for the next phase of Shopping @ Reddit. Move catalog onboarding from days to hours through better error handling, automated feed-issue resolution, productID/item-group-ID matching improvements, and (longer-term) URL-to-catalog automation. Stand up the foundations of a Reddit Merchant Center. - Ship the next phase of catalog innovation. Drive LLM-based catalog enrichment (fill missing attributes, improve descriptions, derive gender/age/category), catalog-driven ad overlays ("Popular with Redditors", "Top Pick", price/promo), and Catalog Insights that show advertisers how their products perform organically and paid on Reddit. Help advertisers with catalog diagnostics to improve performance on ads and organic offerings. - Own the Catalogs & Applied PKG vision. Define the 1–3 year strategy that turns Catalogs into a platform - the spine connecting Reddit's paid and organic Shopping surfaces - Unlock new advertiser demand through catalog capabilities. Land Limitless Catalogs (20M+ product catalogs for large retailers and marketplaces), regional metadata for global clients, and the Shopify integration that expands SMB Shopping on Reddit. - Build the Universal Catalog and Applied PKG. Collaborate with content understanding teams to connect ad catalogs to the Product Knowledge Graph and organic product mentions on Reddit. - Be the Shopping platform voice across Reddit. Represent Catalogs and Applied PKG in Shopping leadership reviews and exec readouts. What You Bring: - Experience: 5+ years of Product Management experience. At least 3 years in AdTech, retail media, marketplaces, or shopping/e-commerce platforms. - Commerce / Product Understanding : Experience with product knowledge graphs, product entity resolution, or product taxonomies at scale. An understanding of how digital shopping works across either organic or paid products. - AI fluency. Comfortable with creating scalable agentic workflows, using AI for data analysis, task automation and more. Evidence of building AI products - either at work or as hobby. - 0-1 instincts paired with execution rigor. You can scope an MVP, ship it, and then operate it. You've done both - built net-new and improved a running production system. - Cross-functional leadership. You've delivered initiatives that span 3+ engineering teams plus PMM, Sales, and Ops. You communicate effectively with executives and earn trust with senior engineers. - Bias to action. Comfortable making decisions with imperfect information, making reasonable risk/reward tradeoffs, and recovering fast when wrong. Nice to Have: - ML fluency. You've shipped ML-powered products in ads, content personalization, retrieval, ranking, or content understanding. You can reason about retrieval, candidate selection, ranking signals, and the tradeoffs between LLM-derived features and traditional features. You don't need to write the model; you need to know enough to lead the people who do. - Experience with LLM-driven content understanding or feature engineering. - Experience shipping for SMB-via-platform channels (Shopify, WooCommerce, BigCommerce). - Experience building or operating a Merchant Center, catalog QA tool, or advertiser-facing data console. Perks and Benefits: - 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago) - Competitive salary and equity options - Comprehensive health benefits (medical, dental, vision) & workplace perks (home office set up stipend etc) - Generous 401k matching - Flexible vacation policy - Paid parental leave (4+ months) - Family planning support - Paid volunteer time off LI-AS1 Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $190,800 - $267,100 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . About the Team: The Brand Ad Formats team drives the development of ad formats that help advertisers maximize reach and brand impact. They focus on high-visibility, awareness-driven solutions that create memorable experiences for Reddit users. By delivering guaranteed placements and engaging ad interactions, they support major brand initiatives and help advertisers achieve measurable outcomes. The team is building fully customizable interactive formats and AI-driven ads that incorporate User-Generated Content (UGC). Moving forward, we will be doubling down on Video Ads , with the goal of turning Reddit into an industry leader and a ‘must buy’ for advertisers to promote video content. As a Staff Android Engineer , you will lead the technical strategy to turn Reddit’s Video Ads into a premier offering for brand advertisers. You will also build and provide technical guidance on new reddit-unique ad formats on Android, ensuring they are high performance, high quality and scalable. What you’ll do: - Video Ads Tech Lead: Partner closely with Product and Design to build a roadmap that will transform our Video Ads format into an industry leader in the space, and drive the technical design and execution of projects that turn the roadmap into reality. - Technical Strategy: Provide guidance to the team working on building video ads as well as reddit-unique ad formats that scale to millions of users, by establishing Android best practices and providing design reviews. - Full-Cycle Leadership: Drive the entire development lifecycle—from early-stage discovery and prototyping to testing, data-driven experimentation, and deployment. - Raise the Bar: Mentor senior engineers across teams in ad formats and establish best practices for design, testing and operational excellence, while also leading by example in understanding and advocating for our customers. What we expect from you: - 8+ years of software engineering experience (Staff level seniority). - Android Mastery: (Minimum of 3+ years) Deep expertise in Kotlin and modern Android architectural patterns. Completed 4+ Android development projects from ideation to deployment in production. - Prior experience in Ad Tech , building highly interactive/rich-media mobile experiences. - Product Mindset: Proven track record of delivering user-facing features where UI polish and performance are critical. - System Design: Ability to navigate complex, data-intensive environments and build fault-tolerant client-side systems. - AI : Experience leveraging GenAI tools to increase software engineering productivity. - Experimentation/Analysis: Fluency working with product metrics, designing and analyzing experiments with exposure to tools like BigQuery, HEX, Firebase, etc. - Versatility: An openness to work across the stack when necessary and explore innovative approaches (e.g., AI/ML integration). - Entrepreneurial spirit: You must be self-directed, innovative, and biased towards action. You live to build new things and thrive in ambiguity. - Excellent communication skills: You must be able to collaborate with teams in a fully remote environment, and discuss complex topics with technical and non-technical audiences. - An experienced technical leader with a strong track record of mentoring and uplifting team members technical skills and aptitude. - Strong organizational skills, the ability to prioritize tasks and keep projects on schedule for the team. - BS degree in Computer Science, similar technical field of study, or equivalent practical experience. Bonus points: - Experience working on Video Ads - Experience working at a scaled peer company - Experience with Jetpack Compose Benefits: - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k with Employer Match - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave LI -Remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $217,000 - $303,900 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence Team Overview We are building the next generation of ML research tools and agentic AI platforms that power machine learning development across Reddit. Our mission is to accelerate the Ads ML lifecycle – from experimentation and training to deployment, evaluation, and autonomous operations – through scalable platform services, intelligen...

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities, built on shared interests, passion, and trust. Our Shopping Ads team builds relevant, performant, and scalable commerce advertising experiences that help advertisers connect products with people who are likely to find them useful. As a Staff Machine Learning Engineer on Shopping Ads, you will lead the technical strategy and execution for the models that power Shopping Ads delivery. You will work across targeting, retrieval, ranking, engagement and conversion prediction, feature engineering, and online serving to improve advertiser outcomes across Dynamic Product Ads and Product Listing Ads. This is a hands-on technical leadership role for an engineer who can translate business goals into an end-to-...

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability whil...

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a Senior Staff Data Scientist to lead the scientific strategy behind Reddit’s ads measurement and signal systems. This role sits at the center of how Reddit proves advertiser value, improves signal quality, builds privacy-aware measurement systems, and connects ads exposure to real advertiser outcomes. As a Senior Staff Data Scientist for Ads Measurement, you will be the principal architect of our technical vision and the driving force behind the next generation of our measurement ecosystem. In a landscape rapidly shifting due to privacy regulations, browser changes, and evolving platform dynamics, you will spearhead innovation across experimental design (incrementality/lift), identity, sig...

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team Description This role sits in the Ads Optimization organizations, which are responsible for the health and performance of Reddit’s ads marketplace. We focus on: - Designing the auction and bidding mechanisms that decide which ads show to which users and at what price. - Building optimization systems that help advertisers achieve their goals (e.g., conversions, ROAS) under budget and delivery constraints. - Ensuring marketplace quality by improving user experience with ads, fighting ad blindness, and increasing valuable ad opportunities on the platform. You’ll join a set of tight-knit engineers working on high-impact, internet-scale problems at the core of Reddit’s revenue engine, collaborating closely with Product, Data Science, and Infra partners across Reddit Ads. Role Description We are hiring Machine Learning Engineers (IC4) to build and evolve the auction, bidding and budgeting systems that power Reddit Ads. In this role, you will: - Design and implement optimization algorithms for auctions, bidding strategies, and pacing that balance advertiser performance, user experience, and marketplace efficiency. - Own systems end-to-end: from problem formulation and algorithm design to experimentation, production deployment, and ongoing iteration. - Work across Ads Optimization (bid strategies, budget optimization, pacing) to deliver measurable wins for advertisers and Redditors. We are hiring a Senior (IC4) level: - IC4 MLEs lead more complex or multi-quarter initiatives, set technical direction for key parts of the bidding/auction/pacing stack, and mentor other engineers while remaining hands-on. Responsibilities Auction, Bidding, and Pacing Systems - Design and implement models and policies that: - Compute bids for different optimization objectives (e.g., CPC, CPA, ROAS-based strategies). - Pace budgets smoothly over time across accounts, campaigns, and ad groups while preventing overspend or underspend. - Allocate spend and auction participation intelligently across segments, surfaces, and time zones. - Translate product

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. Team Overview We’re building a scalable feature platform that powers Ads ML by making high-quality features and training datasets easy to build, share, and maintain. Our small but growing team works on projects like batch & realtime feature management platform, training set generation platform, sequence features platform and, agentic and automated ML workflows for feature lifecycle management. We are looking for an engineer with experience in building high-scale data infrastructure and exposure to ML platforms to help evolve and scale our feature management systems. This is not a pure ML modeling role. The ideal candidate is excited about building reliable infrastructure, data pipelines, and developer-facing tools that make ML engineers more productive. What You’ll Do - Design and build data infrastructure that supports large-scale feature and training set computation, transformation, and storage. - Develop frameworks for batch and real-time features with a focus on reliability, scalability, and ease of use. - Build platform capabilities for feature governance, including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning - Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems. - Build systems that support agentic ML workflows, including automated feature discovery, feature quality evaluation and feature lifecycle management - Contribute to operational excellence through observability, performance tuning, reliability engineering, and cost optimization initiatives. What You Bring - 3+ years in data infrastructure/platform engineering or ML infrastructure platforms. - Hands-on experience building production services, data pipelines, APIs, workflow systems, or developer tools. - Experience with at least one distributed data or compute system such as Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery, or similar technologies. - Familiarity with ML data workflows such as feature generation, training dataset creation, batch processing, real-time data processing, model training, experimentation, or online serving. - Strong coding skills and ability to

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence. About the Role Reddit is building a dedicated Ads ML Efficiency function to make model training and inference materially faster, cheaper, safer, and more scalable. As the Engineering Manager for this team, you will lead a group focused on model optimization, training efficiency, GPU enablement, load testing, model performance tooling, and efficiency guardrails across Ads ML. This role sits at the intersection of ML modeling, systems optimization, and organizational leverage. You will partner closely with ranking teams, ML Platform teams and serving owners to identify the highest-value bottlenecks, land measurable efficiency wins, and build the tooling and operating mechanisms that make those wins repeatable. What you’ll do: - Lead & Grow: Hire, mentor, and retain a high-performing team of ML engineers / systems-oriented engineers working on model optimization and ML efficiency. - Set Technical Direction: Define the roadmap for training optimization, inference optimization, launch-readiness tooling, and reusable efficiency primitives across Ads ML. - Deliver Measurable Wins: Drive reductions in model training time, online latency, serving cost, and infra-driven launch risk. - Build Systems and Tooling: Guide the development of profiling, benchmarking, load testing, observability, cost analysis, debugging, and efficiency certification systems. - Operate in the Critical Path: Partner with model owners and platform teams to accelerate high-priority launches and remove bottlenecks from the path to production. - Shape the Team’s Evolution: Balance near-term white-glove optimization work with medium-term platformization and automation. - Build XFN Alignment: Work closely with MLP, AMP, Ranking, and serving teams to clarify boundaries, upstream generic wins, and keep Ads needs on track. - Raise the Bar: Establish engineering rigor around measurement, performance debugging, launch safety, and technical decision-making for efficiency work. What we’re looking for: <li&gt

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team overview: The Engagement Modeling Team at Reddit focuses on building machine learning models to drive on-platform user engagement with diverse media and content, with a focus on predictive modeling to improve interactions of click-throughs and video view-throughs. This role offers a unique opportunity to shape and scale Reddit’s Ads prediction models, in alignment with our product goals and driving SoTA modeling advancement. This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders. We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S. Responsibilities: - Set Technical Vision and Strategy: Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives. - Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness. - Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence. - Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs. - Innovate in ML Architecture: Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques. Candidate Profile: The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have: - People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth. - Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives. - Drive Technical Execution: Oversee the model development lifecycle from ideati

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence. About the Role Reddit is building a dedicated Ads ML Efficiency function to make model training and inference materially faster, cheaper, safer, and more scalable. This person will be a key senior engineer on that team, owning meaningful efficiency work across training systems, inference and serving paths, launch-readiness tooling, and reusable optimization capabilities for Ads ML. This role sits at the intersection of ML modeling, systems optimization, and engineering leverage. The engineer will partner closely with ranking teams, serving owners, and ML Platform to identify important bottlenecks, land measurable efficiency wins, and help build the mechanisms that make those wins repeatable. What you’ll do - Independently own high-value optimization initiatives across training, inference, or launch-readiness for important Ads ML workloads. - Diagnose bottlenecks in real production systems using profiling, benchmarking, and observability rather than intuition-first debugging. - Build performance tooling, optimization playbooks, observability hooks, guardrails, or efficiency primitives that help more than one team or workload over time. - Improve launch-safety and efficiency readiness by contributing to load testing, fallback readiness, latency and cost visibility, and operational confidence for heavy models. - Work with model owners and platform teams to land pragmatic fixes while helping the team gradually standardize repeated solutions. - Contribute to the team’s technical direction by surfacing patterns, tradeoffs, and opportunities for reuse or automation. - Mentor less-experienced engineers through code, debugging, measurement rigor, and strong execution habits. What we’re looking for - Deep ML systems experience close to real production models and workloads, not just generic infra exposure. - Direct hands-on experience improving training or serving efficiency with measurable outcomes. - Strong technical judgment across model-level, runtime-level, and infrastructure-level optimization choices. - Ability to own complex projects end to end and collaborate effectively across team boundaries. - Good customer and platform instincts: can solve concrete bottlenecks while keeping maintainability, adoption, and future reuse in mind. - Strong communication: able to explain tradeoffs clearly to engineers and partner teams. Nice-to-have - Experience with GPU training or serving migrations. - Experience with PyTorch, distributed training frameworks, or kernel/runtime optimization. - Experience building launch certification, efficiency benchmarking, or cost observability systems. - Experience in organizations where platform and applied modeling responsibilities are split across multiple teams. - Experience with model compression or deployment optimizations such as quantization, pruning, distillation, or checkpoint optimization. Benefits: - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k with Employer Match - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $216,700 - $303,400 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s lower funnel business is rapidly growing and pushing the heavy ranking web conversion models towards state-of-the-art is critical for continued growth. The Conversion modeling Team plays a pivotal role in developing and maintaining machine learning models that drive user conversions from Reddit Ads, with a special focus on predictive modeling around interactions like purchase, signup, add to cart, and other lower funnel user actions. As we expand our machine learning infrastructure and incorporate new engagement signals, we are looking for a skilled Engineering Manager who can lead this critical team. This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders. We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S. Target Skills and Expertise The Engineering Manager (EM) will be responsible for defining the team’s vision, setting strategic direction, and executing a technical roadmap for conversion modeling at Reddit. This involves: - Model Architectures: Expertise in architecting and implementing deep learning models, with experience in ranking, recommendation, or conversion modeling. - ML Frameworks: Proficiency with mainstream ML libraries (TensorFlow, PyTorch). - End-to-End ML Lifecycle: Experience in training, testing, and deploying production-grade machine learning models. - Data Pipelines: Experience orchestrating large-scale data generation and processing pipelines. - Ads domain Experience: Experience in interaction of ranking model with rest of Ads systems like bidding, auction, retrieval etc - Ads Modeling (Preferred): Background in ads modeling or familiarity with engagement prediction models in the ads domain is beneficial. Role responsibilities: The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have: - People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth. - Set Technical Vision and Strategy: Abilit

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Position Overview We're seeking a highly motivated and analytical Senior, Business Risk and AI Automation, to play a pivotal role in building an AI-first internal audit and risk function. This role is the first of its kind and an opportunity for an audit individual with a passion for technology and innovation to drive the future of assurance and risk through AI and automation. You will be at the forefront of our efforts to build and scale an industry-leading AI assurance program. While your initial focus will be on leveraging agentic AI to transform SOX testing, you'll have opportunities to impact cross-functional areas including core financial processes and platform regulatory risks and more. If you're eager to join a team that's shaping the future of risk and automation and influencing how mission-driven organizations operate, this is the perfect opportunity for you! What You’ll Do - Architect and scale our SOX compliance program by designing, developing, and maintaining AI-driven testing that enhances accuracy, provides real-time insights, and reduces manual overhead. - Spearhead the testing of core business process controls (e.g. financial reporting, revenue recognition, payroll and equity compensation, etc.) using agentic AI systems to identify and mitigate potential threats. - Collaborate cross-functionally with Finance and Accounting, Sales, People & Culture, Legal, and other key stakeholders to strengthen controls and drive business process improvements. - Serve as a subject matter expert and champion for the use of AI and automation in risk management. - Contribute to a culture of innovation and excellence within the Risk Advisory and Assurance team. Who You Might Be - An experienced professional with 2 to 4 years of experience in a Big 4 accounting firm, internal audit, and/or compliance function with a demonstrated passion for technology and automation. - A subject matter expert with experience supporting internal controls and SOXtesting in the technology industry, preferably platform companies. - A self-motivated, results-oriented technology-first thinker with a proactive and creative approach to problem-solving. You seek "what could be" and are driven to build it. - A collaborator with a strong work ethic and enthusiasm for learning, who thrives in a fast-paced, dynamic environment. Knowledge, Skills, and Abilities - Professional certifications such as CPA, CIA, CISA, and/or CISSP preferred - Controls testing experience, including business process controls, entity-level controls, application controls, and key reports. - Ability to assess complex processes to identify risks and opportunities for automation - Hands-on experience leveraging AI tools and prompting (i.e., Google AI suite, ChatGPT, specialized AI audit tools, etc) - Critical thinker that can focus on solutions and comfortable with ambiguity Benefits - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Comprehensive Medical Benefits & Health Care Spending Account - Registered Retirement Savings Plan with matching contributions - Income Replacement Programs - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Position Overview We're seeking a highly motivated and analytical Senior, Business Risk and AI Automation, to play a pivotal role in building an AI-first internal audit and risk function. This role is the first of its kind and an opportunity for an audit individual with a passion for technology and innovation to drive the future of assurance and risk through AI and automation. You will be at the forefront of our efforts to build and scale an industry-leading AI assurance program. While your initial focus will be on leveraging agentic AI to transform SOX testing, you'll have opportunities to impact cross-functional areas including core financial processes and platform regulatory risks and more. If you're eager to join a team that's shaping the future of risk and automation and influencing how mission-driven organizations operate, this is the perfect opportunity for you! What You’ll Do - Architect and scale our SOX compliance program by designing, developing, and maintaining AI-driven testing that enhances accuracy, provides real-time insights, and reduces manual overhead. - Spearhead the testing of core business process controls (e.g. financial reporting, revenue recognition, payroll and equity compensation, etc.) using agentic AI systems to identify and mitigate potential threats. - Collaborate cross-functionally with Finance and Accounting, Sales, People & Culture, Legal, and other key stakeholders to strengthen controls and drive business process improvements. - Serve as a subject matter expert and champion for the use of AI and automation in risk management. - Contribute to a culture of innovation and excellence within the Risk Advisory and Assurance team. Who You Might Be - An experienced professional with 2 to 4 years of experience in a Big 4 accounting firm, internal audit, and/or compliance function with a demonstrated passion for technology and automation. - A subject matter expert with experience supporting internal controls and SOXtesting in the technology industry, preferably platform companies. - A self-motivated, results-oriented technology-first thinker with a proactive and creative approach to problem-solving. You seek "what could be" and are driven to build it. - A collaborator with a strong work ethic and enthusiasm for learning, who thrives in a fast-paced, dynamic environment. Knowledge, Skills, and Abilities - Professional certifications such as CPA, CIA, CISA, and/or CISSP preferred - Controls testing experience, including business process controls, entity-level controls, application controls, and key reports. - Ability to assess complex processes to identify risks and opportunities for automation - Hands-on experience leveraging AI tools and prompting (i.e., Google AI suite, ChatGPT, specialized AI audit tools, etc) - Critical thinker that can focus on solutions and comfortable with ambiguity Benefits - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Comprehensive Medical Benefits & Health Care Spending Account - Registered Retirement Savings Plan with matching contributions - Income Replacement Programs - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City & Chicago) our doors are open for you to come into the office as often as you'd like. About the Role: The Safety ML team is hiring a Machine Learning Engineer to build and iterate on the next generation of safety systems at Reddit. In this pivotal role, you will be responsible for developing, training, and optimizing state-of-the-art large language models (LLMs) in order to scalably and efficiently support the enforcement of Reddit Rules. You will be partnering closely with other Safety teams (Operations, Engineering, Product, Data Science) at Reddit to identify and build solutions that will help keep users safe as Reddit grows. Responsibilities: - Design, develop, optimize and deploy ML models, including large language models, for various natural language processing tasks. - Implement and maintain training pipelines, leveraging distributed training and optimizing for performance and efficiency. - Collaborate with cross-functional teams to gather requirements, define model architectures and iterate on model development. - Conduct model evaluations, performance analysis, and optimization to improve model accuracy and reduce biases. - Stay up-to-date with the latest research and advancements in the field of natural language processing, multimodal signals, and large language models. - Contribute to the development of best practices, guidelines, and ethical AI principles for responsible ML development and deployment. Required Qualifications: - 5+ years of relevant MLE experience in natural language processing, deep learning, and AI model development. - Strong background in Python programming and deep learning frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. - Expertise in distributed training frameworks (e.g., Ray Training, PyTorch Distributed), and efficient utilization of hardware resources. - Proficiency in data preprocessing, tokenization, embeddings, and language modeling techniques. - Passion for developing scalable, well-designed, and responsible AI solutions that positively impact society. - Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams. - Entrepreneurial spirit, self-motivation, and a bias towards action in fast-paced environmen LI-SP1 Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $216,700 - $303,400 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Notifications Relevance team at Reddit is building the next generation of notifications focused on delivering the right content to the right user at the right time using the right channel (push notification, email digest and in-app). We are the second largest growth lever at Reddit and a core component to understanding how to delight our current user base and bring new users to discover all that Reddit has to offer. Reddit is home to some of the most valuable and engaging conversations on the internet. As a Staff Machine Learning Engineer on Notifications Relevance , you'll serve as a technical leader for one of Reddit's highest-leverage ML systems, helping millions of users discover relevant content, communities, and conversations every day. You'll drive the strategy, architecture, and execution of large-scale recommendation systems spanning targeting, budget optimization, retrieval, ranking, measurement, and emerging LLM-powered experiences. This role offers the opportunity to shape the future of engagement and retention at Reddit while pushing the boundaries of personalization and machine learning at massive scale. What You’ll Do - Contribute to advancing Reddit's growth by designing and implementing content discovery algorithms that prioritize a seamless and highly personalized user experience. - Deeply understand the Reddit Notifications product and drive the vision for the notifications relevance team. - Enhance core recommendation capabilities, including candidate retrieval, ranking models, and budgeting optimization, while designing and testing new pipeline components. You will also deploy ML models, integrate LLMs, and ensure robust monitoring and smooth product integration throughout the process. - Serve as the primary ML domain expert, deploying state-of-the-art models at scale, driving architectural decisions, and ensuring robust monitoring and smooth product integration across the engineering organization. - Collaborate across disciplines and with ML, Product, Infrastructure, and DS teams at Reddit to find technical solutions to complex challenges Who You Are - 8+ years of industry experience with deep expertise in large-scale recommendation systems, notifications experience preferred. - Proven ability to identify key opportunities, define roadmaps and drive scalable improvement in notifications relevance. - Strong experience in building and deploying large-scale ML models using frameworks such as PyTorch or Tensorflow.</l

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We are hiring Machine Learning Engineers across our Consumer Engineering organization, giving you the opportunity to work on a wide range of high-impact problems across the Consumer ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On We are looking for a Staff Machine Learning Engineer to help drive the next generation of Reddit’s ML ecosystem across recommendations, search, messaging, and foundational AI systems. You will lead high-impact initiatives from ideation to production, shaping both technical strategy and product direction across multiple ML domains. This is a highly cross-functional role partnering with Product, Data Science, and Engineering to deliver meaningful user and business impact. This role sits at the intersection of: - Relevance & recommendation systems (content, search, notifications) - AI-powered discovery & LLM-driven experiences - Content and user understanding & large-scale representation learning - Large-scale ML infrastructure and pipelines What You’ll Do - Lead end-to-end ML initiatives from ideation through production and iteration, shaping technical direction and translating product goals into scalable solutions - Architect, build and deploy large-scale ML systems across recommendation, search, and content/user understanding, including retrieval/ranking models, representation learnings embeddings optimizations, and LLM or GenAI-powered capabilities - Drive measurable impact on user engagement, discovery, and long-term value - Collaborate with cross-functional teams to align product and technical roadmaps and unlock key future ML capabilities - Stay at the forefront of AI research, evaluating and introducing new AI/ML paradigms to keep Reddit’s ML ecosystem at

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Notifications Relevance team at Reddit is building the next generation of notifications focused on delivering the right content to the right user at the right time using the right channel (push notification, email digest and in-app). We are the second largest growth lever at Reddit and a core component to understanding how to delight our current user base and bring new users to discover all that Reddit has to offer. Redditors produce the most amazing content about every niche topic in the world. Leveraging machine learning and large-scale system development, we process hundreds of millions of posts and user activities to provide personalized recommendations for tens of millions of users. As a Senior Staff, you will design and build a large-scale system that powers end-to-end recommendation systems at scale. You’ll work across multiple areas of the stack, including budget optimization, retrieval, ranking, features, measurement, LLM-based answers, etc, partnering deeply with product, org leads, and other XFN to deliver reliable, high quality systems that can help Reddit Notifications push the boundary on state of the art. What You’ll Do - Contribute to advancing Reddit's growth by designing and implementing content discovery algorithms that prioritize a seamless and highly personalized user experience. - Deeply understand the Reddit Notifications product and drive the vision for the notifications relevance team. - Enhance core recommendation capabilities, including candidate retrieval, ranking models, and budgeting optimization, while designing and testing new pipeline components. You will also deploy ML models, integrate LLMs, and ensure robust monitoring and smooth product integration throughout the process. - Serve as the primary ML domain expert, deploying state-of-the-art models at scale, driving architectural decisions, and ensuring robust monitoring and smooth product integration across the engineering organization. - Collaborate across disciplines and with ML, Product, Infrastructure, and DS teams at Reddit to find technical solutions to complex challenges. - Mentor and guide senior and staff engineers in the team. - Partner closely with senior leadership and cross-functional org leads to shape long-term roadmaps, balancing immediate operational wins with strategic technical objectives. Who You Are - 10+ years of industry experience with deep expertise in large-scale recommendation systems, notifications experience preferred. - Proven

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Search Recommendations & Relevance team at Reddit is building the next generation of search - one that goes beyond “10 blue links” to deliver real answers, perspectives and conversation from the world's largest corpus of human conversation. We power both Reddit Search and our AI-native Search experience, redefining how users discover and interact with information. Redditors produce the most amazing content about every niche topic in the world – this underleveraged data coupled with modern advances in AI systems is presenting a unique opportunity to quickly build a new kind of search engine. As a Senior Staff, you will design and build a large-scale system that powers end-to-end search relevance at scale. You’ll work across multiple areas of the stack, including query understanding, retrieval, ranking, features, measurement, LLM-based answers, RAG etc, partnering deeply with product, org leads, and other XFN to deliver reliable, high quality systems that can help Reddit Search scale to billions of users. What You’ll Do - Contribute to advancing Reddit's Search and Recommendations products by designing AI-driven Search experience prioritizing seamless and delightful user experience. - Deeply understand the Reddit search product and drive the vision for the search relevance team. - Enhance core search retrieval and ranking, design and implement new search engine features, build and scale search indexes, develop and test new pipeline components. You will also deploy ML models, integrate LLMs, and ensure robust monitoring and smooth product integration throughout the process. - Collaborate across disciplines and with ML, Product, Infrastructure, and DS teams at Reddit to find technical solutions to complex challenges. - Mentor and guide senior and staff engineers in the team. - Influence org-wide technical direction and partner closely with senior leadership to shape the long-term roadmap Who You Are - 10+ years of industry experience with deep expertise in large-scale search and recommendation systems. - Proven ability to identify key opportunities, define roadmaps and drive scalable improvement in search relevance. - Strong experience in building and deploying large-scale ML models using frameworks such as PyTorch or Tensorflow. - Experience working with LLM in production, including evaluation, tuning and deployment. &lt

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The GenAI Security team within Reddit’s Security, Privacy, Assurance, and Corporate Engineering organization protects Reddit’s GenAI usage across employee tools, internal agents, and production user-facing systems. Our mission is to secure and protect Reddit’s AI traffic and GenAI adoption by default. We are building zero-trust, defense-in-depth systems that verify identity, permissions, data access, and semantic intent across AI workflows. A core part of this work is developing practical, high-quality ML models that detect and prevent security risks such as prompt injection, jailbreak attempts, sensitive data exfiltration, unsafe model behavior, anomalous usage, and unauthorized agent actions. We are looking for a Senior Machine Learning Engineer to lead model development for GenAI Security and help establish strong ML practices across SPACE. This role owns the full machine learning lifecycle: problem definition, data ETL, feature engineering, model training, model evaluation, deployment, experimentation, prediction, monitoring, debugging, and retraining. What You’ll Do - Build and improve security-focused ML models for Reddit’s GenAI traffic, including guardrail models, semantic classifiers, anomaly detection models, and other neural network based security signals. - Own model development end to end: define the security problem, assemble and label datasets, build ETL pipelines, engineer features, train models, evaluate quality, deploy to production, monitor performance, and retrain from production feedback. - Use modern deep learning architectures, including neural networks, transformers, sequence models, embeddings, and model distillation where they are the right practical fit. - Design rigorous evaluation suites for adversarial examples, hard negatives, long-context inputs, structured payloads, tool calls, multi-turn workflows, and real production traffic. - Improve model precision, recall, latency, cost, calibration, and operational reliability for high-impact production surfaces. - Build repeatable MLOps workflows for SPACE, including training pipelines, model lineage, artifact management, holdout evaluation, dashboards, rollback paths, and retraining loops. - Partner closely with ML Infrastructure, LLM Gateway, DevX, Ads, Answers, Safety, Privacy, Compliance, and other Security teams to bring security models into real production workflows. - Work pragmatically with Reddit’s evolving ML platform, using existing infrastructure where possible and building focused tooling when needed to keep model iteration moving. - Translate security goals into me

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. About the Team The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company’s ML ecosystem. Responsibilities - Design and build systems that improve the efficiency of ML training and inference workloads. - Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance. - Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization. - Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements. - Build benchmarking frameworks and performance dashboards for training and serving systems. - Optimize distributed training infrastructure, data pipelines, and model serving architectures. - Lead cross-functional initiatives that improve the productivity of Reddit ML engineers. - Drive technical strategy for ML platform scalability, reliability, and cost efficiency. Qualifications Required - BS, MS, or PhD in Computer Science or a related field. - 5+ years of software engineering experience. - Strong proficiency in Python - Profiency in at least one systems language (Go, C++, Rust, or Java) preferred - Experience building distributed systems at scale. - Experience with machine learning infrastructure, training systems, or model serving platforms. - Deep understanding of performance engineering and systems optimization. - Strong debugging and profiling skills. Preferred - Experience with large-scale recommendation, ranking, generative AI, or foundation model systems. - Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark - Familiarity with GPU architectures and performan

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . About The Role Reddit is a community of communities. It is built on shared interests, passion, and trust and is home to some of the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. Reddit is hiring a Senior Security Engineer, AI Security to help teams build and ship AI-powered products securely. This role combines product security judgment with hands-on engineering to secure the systems, tools, and workflows behind Reddit's AI efforts. You will review AI-powered product designs, threat model LLM and agentic workflows, and build reusable security primitives that make secure AI development easier for teams across Reddit. This is not an MLE role, but you should be comfortable reasoning about how AI systems fail, how agents use tools, and how security controls fit into inference, retrieval, tool-use, and execution paths. The best candidates combine practical application security judgment with strong builder instincts. They can identify risks before launch, then turn repeated findings into guardrails, scanners, registries, sandboxes, libraries, policy checks, or platform controls that scale beyond one product team. What You'll Do - Review and threat model AI-powered product features, LLM integrations, agentic workflows, MCP servers, tools, plugins, retrieval systems, model outputs, and internal AI tools before launch. - Build reusable AI security primitives such as guardrails, scanners, policy checks, tool-use controls, registries, sandboxes, libraries, and workflow-native enforcement points. - Design security tooling that can sit in the inference, retrieval, or execution path to detect and prevent prompt injection, jailbreaks, tool misuse, data leakage, unsafe code generation, and suspicious agent behavior. - Partner with teams building products and platforms with AI to define practical security controls that fit how they design, build, and ship. - Proactively find, fix, and prevent AI security issues, while making any required product or engineering changes clear and low-friction for partner teams. - Turn one-off AI security issues into systemic fixes, paved paths, measurable controls, and reusable guidance. What We're Looking For - 5+ years of experience in product security, application security, software security, security engineering, backend engineering, or security platform engineering. - Strong application sec

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible first workforce! The Ads Measurement Org is dedicated to enhancing the efficiency and user-friendliness of our advertising platform. The Measurement Modeling team owns all the Machine Learning solutions for Ads Measurement, including Identity Matching, Identity Graph, Utility Enhancement for Ads Privacy, Modeled Conversion, and new Measurement Modeling Initiative. As critical and complex part, in Identity Modeling, we are building new advanced machine learning solutions, the space resides in intersection of ads stack that interacts with various upstream and downstream systems, it serves critical business needs for monetization and consumer as well, including Measurement & Reporting, Experimentation, Personalization, Delivery, and Safety etc, requires major XFN as well as cross team/org collaborations. We are looking for an IC5 Staff ML Engineer of Ads Identity Modeling, to define long term direction and drive architecture evolution, be responsible for engineering quality and enforce best practice, lead new exploration and cross-org collaboration in new modeling initiatives, and champion ML/AI innovation to ensure the solutions utilize SOTA ML technology. Our diverse group of engineers, product managers, data scientists, and ads specialists is excited to welcome you on board! Minimum Qualifications: - 7+ years of professional software engineering experience, with at least 3+ years focused on ML-driven systems at scale - Demonstrated experience architecting and building ads measurement modeling solutions leveraging advanced machine learning techniques - Strong knowledge of various identifiers (cookies, hashed emails, phone numbers, IP addresses, user agents) and their use in identity resolution - Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference - Solid understanding of large-scale data processing, distributed computing, and data infrastructure (e.g., Spark, Kafka, Beam, Flink) - Proven technical leadership in cross-functional settings, driving architectural decisions and influencing stakeholders (product, data science, privacy, legal) - Excellent communication, mentoring, and collaboration skills to align teams on a long-term vision for identity resolution Responsibilities: - Lead the technical strategy and architecture for our company’s ads identity modeling solutions and other related ads measurement models - Design and train advanced ML mod

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Software Engineer, you will lead the development of a large-scale GenAI Platform at Reddit. - Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability. - Designed and developed ML and Generative AI systems in cloud-based production environments at scale. - Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines. - Implement and operationalize agentic AI workflows with tool use using frameworks such as LangChain and LangGraph. - Drive adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management. - Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production. - Strong ownership mindset and platform thinking. - Ability to lead AI platform delivery from concept to production. Who You Might Be: - 5+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles. - Have experience operating orchestration systems such as Kubernetes at scale - Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more - Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc. - Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders - Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the genAI product development lifecycle. - Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems is a plus &

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team Description: The Ads Marketplace team is a strategic growth engine for Reddit Ads. Our mission is to democratize high-performance advertising by enabling brands to achieve world-class results with minimal friction. To achieve this, we need an incredibly robust, scalable, and state-of-the-art Machine Learning infrastructure. The Ads ML Platform team is at the core of this mission, tasked with building the foundation that powers all of our content understanding, ad targeting, and ad ranking models. We are empowering our ML engineers and data scientists to move faster and build smarter. The Role: As the Staff Product Manager for the Ads ML Platform, you will hold significant ownership over the infrastructure and tools that make our ads marketplace intelligent. You will define the vision and build the roadmap for a platform that enables unparalleled engineering velocity and supports the most modern ML architectures. You will be the bridge between complex ML systems and business outcomes. Whether it's integrating generative AI to increase developer productivity, establishing unified model-serving infrastructure, or optimizing GPU utilization, your work will directly accelerate how quickly and effectively we can ship highly-performant ad products. If you are passionate about the intersection of platform engineering and state-of-the-art ML research, this is the role for you. Responsibilities - Define the Vision: Shape the long-term strategy and roadmap for Reddit’s Ads ML platform, ensuring we are adopting cutting-edge technologies (including Generative AI and LLM workflows) to stay ahead of the curve. - Accelerate Velocity: Build products and tooling that dramatically reduce friction for Machine Learning Engineers (MLEs) and Data Scientists, enabling them to train, deploy, and iterate on models faster than ever. - Cross-Functional Leadership: Partner deeply with Engineering, Data Science, and Ads Product teams to understand their constraints, prioritize platform initiatives, and deliver scalable infrastructure. - Drive Execution and Adoption: Own key performance indicators (KPIs) around platform reliability, latency, cost-efficiency, usage metrics, and developer productivity. - Stay Cutting-Edge: Keep your finger on the pulse of the broader ML ecosystem. Read the latest research papers, understand emerging architectures, and determine how they can be practically a

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit. - Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more - Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration - Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment - Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more - Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges Who You Might Be: - 5+ years of experience in ML infrastructure, including model training and model deployments - Hands-on experience with ML optimization, including memory and GPU profiling - Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more - Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb) - Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc. - Deep experience working with distributed training frameworks, including Ray and Kubernetes - Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle. - Strong organizational & communication skills - Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus</li

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Benefits: - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Comprehensive Medical Benefits & Health Care Spending Account - Registered Retirement Savings Plan with matching contributions - Income Replacement Programs - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave LI-Remote #LI-NH1 In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . <span style="font-

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. The Ads Foundational Representations (AFR) team develops signals and representations of Reddit’s core entities (ads, posts, users, and so on), capturing the semantic, contextual, and behavioral information that Reddit Ads needs. We work on building embeddings to understand content and users' interests based on the content they engage with. Our team has the potential to highlight one of Reddit's biggest differentiators: genuinely curated, high-quality, extremely relevant, and daily updated organic content. We are a Machine Learning/Data heavy team with a focus on the following areas: - Multimodal & Content Embeddings - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) text and media content by embedding them into a shared space. - Contextual and Behavioral Relevance - Working with Product & Data Science, establishing definitions of what ads are relevant to users and the content we show them next to, building metrics and fine-tuning embeddings to better reflect relevance. - Knowledge Graph Embeddings - Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting & business insights. - User Intent Modeling - Leveraging various techniques to introduce user representations based on the content they interact with: batch & real-time sequence modeling, LLM summarization, etc. - LLM-based Representations - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes The signals and features we create become a key piece in the Ads Delivery funnel, from targeting to the auction, as well as the Business Insights product and other advertiser-facing products such as Creative generation and optimization. As a Senior ML Engineer , you’ll be in charge of the full-cycle execution of ML projects - from collaborating with cross-functional teams on requirements and design, to the implementation of the feature and its experimentation. Responsibilities - Developing new or iterating on existing emb

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: - Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities - Intelligent advertising systems including ranking, bidding, measurement, and optimization - Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals - Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems - Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. What You’ll Do - Design, build, and deploy production-grade machine learning models and systems at scale - Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring - Build scalable data and model pipelines with strong reliability, observability, and automated retraining - Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. - Partner cross-func

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City & Chicago) our doors are open for you to come into the office as often as you'd like. We’re looking for a Director of Machine Learning to lead Reddit’s efforts in building industry-leading ML systems that keep our platform safe and foster healthy online communities. This leader will drive the strategy, development, and deployment of machine learning models that detect and prevent harmful content and behavior at scale. In this role, you will own the roadmap for Safety and moderation ML, lead a team of applied scientists and engineers, and partner cross-functionally across Product, Engineering, Safety operations, Trust & Community, and AI/ML Platform to innovate on real-time detection, automation, and user protection systems. You will leverage modern ML — including fine-tuned LLMs — to ensure Reddit remains a safe, welcoming, and positive environment for our global user base. Responsibilities - Set the vision and strategy for applying ML to Trust & Safety, ensuring scalable, proactive protection against evolving abuse patterns. - Lead and grow a high-performing Safety ML organization, including applied research, model development, productionization, and continuous improvement. - Develop and deploy cutting-edge Safety ML systems (including fine-tuned LLMs and transformer models) that outperform state-of-the-art solutions in quality, latency, and efficiency. - Partner with Trust & Safety, Product, Moderation, and AI/ML Platform teams to identify safety risks, emerging harm vectors, and ML opportunities that improve detection, enforcement, and user experience. - Drive successful experimentation, evaluation, and model lifecycle management, ensuring high precision, recall, explainability, and policy alignment. - Champion ethical and responsible AI practices in all Safety ML solutions. - Track performance through metrics, research-based iteration, and alignment with Reddit’s safety policies and regulatory standards. - Represent Safety ML leadership internally and externally — including conferences, publications, industry groups, and cross-company collaboration initiatives. Required Qualifications <li&

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit's Ads Data Science team is seeking a highly motivated Principal Data Scientist to drive the strategic application of advanced quantitative methods across our advertising platform to advance the intelligence powering the advertiser experience on Reddit. In this pivotal leadership role, you will be responsible for defining and implementing the next generation of foundational data science solutions, leveraging expertise in statistics, econometrics, machine learning and/or other quantitative methods to optimize Reddit's Ads marketplace. You will partner closely with Analytics Engineering to ensure our underlying data systems are continuously upleveled to support advanced analysis and modeling at scale. You will be a strategic partner, collaborating closely with Product, Engineering, and Business leaders to establish the long-term vision for measurement, prediction, and optimization. As a thought leader, you will champion scientific rigor, causal inference, and economic modeling, while providing deep mentorship to the broader team. If you are passionate about applying foundational quantitative science to solve complex, high-impact business problems, join us in shaping the future of Reddit ads. What you’ll do - Define the future of Ads Data Science: Own the design and long-term evolution of our core Ads Data Science solutions and infrastructure, building for the next several years of continued scale, revenue growth, and relevance. - Strategic leadership & scientific roadmap: Identify fundamental gaps and opportunities in our current systems (including platform, auction, targeting, and full-funnel relevance models). Lead the strategic design and scientific roadmap for new solutions to significantly improve Advertiser ROI, User experience, and Reddit revenue. - Drive end-to-end impact: Take end-to-end ownership of complex problem domains such as full funnel acceleration, advertiser lifetime value (LTV), and developing advanced predictive and causal frameworks that power Reddit’s strategic investments. - Establish scientific standards: Define and codify best practices for large-scale statistical modeling, economic analysis, causal inference, offline model evaluation, and A/B experimentation to ensure scientific rigor and trust across the Ads data science and engineering teams. - Technical deep dive & authority: Be the undisputed domain authority for data scientists, engineers, and product managers on complex problems involving large-scale

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Staff ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit. - Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more - Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration - Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment - Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more - Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges Who You Might Be: - 8+ years of experience in ML infrastructure, including model training and model deployments - Hands-on experience with ML optimization, including memory and GPU profiling - Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more - Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb) - Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc. - Deep experience working with distributed training frameworks, including Ray and Kubernetes - Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle. - Strong organizational & communication skills - Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus</li&

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: US remote-friendly Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic. Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. About the Ads Data Science Team: The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling. About the Role: We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit. Responsibilities: - Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform - Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform - Collaborate with product managers and engineers to define product requirements and translate them into data science solutions - Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition - Communicate findings and recommendations to stakeholders across the organization - Stay up-to-date on the latest

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Staff Software Engineer, you will help define and lead the vision for Reddit’s large-scale GenAI Platform, shaping the strategy, architecture, and operating model that enable teams across the company to build, deploy, and scale generative AI products with confidence. Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability. - Lead and execute the vision, strategy, and roadmap for Reddit’s large-scale GenAI Platform. - Define the platform architecture and operating model that enable teams to build, deploy, and scale GenAI products reliably. - Drive the strategy for a unified LAG Gateway supporting internally and externally hosted LLMs through consistent APIs and abstractions. - Set the direction for core platform capabilities such as rate and token limit management, intelligent failover, and production resilience. - Shape Reddit’s approach to an enterprise-grade RAG system - Establish the strategic direction for agentic AI workflows and tool-use patterns across the platform. - Own the end-to-end platform strategy from concept through production adoption and long-term evolution. - Drive MLOps and LLMOps standards across CI/CD, testing, versioning, evaluation, and lifecycle management. - Define best practices for observability, monitoring, governance, and operational excellence across GenAI systems. - Partner across engineering, product, and leadership to align platform investments with company priorities and user needs. - Champion platform thinking with a strong focus on scalability, reliability, performance, and developer experience. - Influence technical direction across teams by turning emerging AI capabilities into a scalable platform strategy. Who You Might Be: - 10+ years of experience in ML Engineering, AI Platform Engineering,

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a Senior Staff Data Scientist to lead the scientific strategy behind Reddit’s ads measurement and signal systems. This role sits at the center of how Reddit proves advertiser value, improves signal quality, builds privacy-aware measurement systems, and connects ads exposure to real advertiser outcomes. As a Senior Staff Data Scientist for Ads Measurement, you will be the principal architect of our technical vision and the driving force behind the next generation of our measurement ecosystem. In a landscape rapidly shifting due to privacy regulations, browser changes, and evolving platform dynamics, you will spearhead innovation across experimental design (incrementality/lift), identity, signals, and privacy-safe 1P/3P measurement. This is a high-visibility, high-impact role requiring a rare blend of deep experimentation & causal inference expertise, strategic foresight, and the ability to influence cross-functional executives and industry standards. You will not just adapt to the changing ad-tech environment, you will redefine how we measure value. Responsibilities - Technical Vision & Strategy: Define the long-term data science vision & strategy across ads measurement, signal quality, identity, attribution, and privacy. Establish how Reddit should evaluate advertiser value, measurement quality, and signal utility across first-party and third-party products. - Set the Cross-Pillar Measurement Science Strategy: Define the long-term data science strategy across ads measurement, signal quality, identity, attribution, and privacy. Establish how Reddit should evaluate advertiser value, measurement quality, and signal utility across first-party and third-party products. - Build Trusted Measurement and Evaluation Frameworks: Create rigorous frameworks for validating lift, attribution, identity quality, modeled conversions, signal loss recovery, and privacy-aware measurement. Define ground truth, objective functions, quality metrics, guardrails, and decision frameworks that guide product and engineering investments. - Advance Experimentation and Causal Inference at Scale: Lead the evolution of Reddit’s experimentation and lift methodologies across Brand Lift, Conversion Lift, Split Testing, and emerging measurement products. Improve study quality, reduce bias and contamination, and develop scalable diagnostics for experiment health, feasibility, and interpretability. Partner with Ads Engineering to operationalize complex causal models, ens

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City & Chicago) our doors are open for you to come into the office as often as you'd like. The AI Engineering team at Reddit is building our own Reddit-native foundational Large Language Models (LLMs). This team sits at the intersection of applied research and massive-scale infrastructure, training models that truly understand the unique culture, language, and structure of Reddit communities. You'll join... Observed freshness date: 2026-07-08T12:17:09-04:00 Freshness signal: first_party_updated_at Remote signal: remote Salary: not published Canonical apply URL: https://job-boards.greenhouse.io/reddit/jobs/7555007 Source URL: https://job-boards.greenhouse.io/reddit

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence Team Overview We are building the next generation of ML research tools and agentic AI platforms that power machine learning development across Reddit. Our mission is to accelerate the Ads ML lifecycle – from experimentation and training to deployment, evaluation, and autonomous operations – through scalable platform services, intelligent automation, and developer-centric tooling. Our team owns critical platform capabilities including offline ML experimentation systems, production training orchestration frameworks, ML lifecycle automation and, agentic ML frameworks that enable faster model iterations. We are looking for an experienced engineer with deep expertise in large-scale distributed systems, ML platforms, and emerging agentic architectures to help define and build the foundational tooling for the next generation of our machine learning devX tooling. What You’ll Do - Design and build large-scale offline ML experimentation platforms that enable reproducible research, model development, evaluation, and promotion workflows. - Develop production-grade training orchestration frameworks supporting distributed training, hyperparameter optimization, model evaluation, and automated retraining. - Build infrastructure for experiment tracking, metadata management, lineage, artifact versioning, model registries, and reproducibility. - Partner with ML engineers and researchers to improve experimentation velocity and operational efficiency. - Build automated workflows for model promotion, rollback, compliance validation, and continuous evaluation. - Design and build an agentic AI execution platform supporting autonomous and human-in-the-loop workflows, including multi-agent orchestration, memory/context systems, and scalable workflow infrastructure. What You Bring - 5+ years in infrastructure/platform engineering or large-scale distributed systems. - 2+ years of hands-on experience building and operating production ML infrastructure, developer SDKs, platform APIs, or self-service AI tooling. - Experience building workflow orchestration systems, developer platforms, or large-scale automation framewor

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: At Reddit we continue to grow our teams with the best talent. We're completely remote friendly . Team Description: The Marketing Science team at Reddit leverages data to maximize the impact of Reddit’s own marketing investments. We serve as the engine behind our growth, using advanced experimentation, causal inference, and econometrics to understand what drives users to Reddit and what brings advertisers to our platform. We work at the intersection of brand building and performance marketing, ensuring every dollar spent is an investment in the long-term health of our ecosystem. Role Description: Reddit is looking for a highly experienced Staff Data Scientist to lead the strategy and technical execution of our Marketing Intelligence efforts. In this role, you will be the primary architect of how we measure and optimize Reddit’s marketing spend. You will focus on two critical flywheels: B2B Marketing (acquiring and retaining advertisers) and B2C Growth (acquiring and engaging new Redditors). This is a high-autonomy, high-impact role where you will set the long-term strategic goals for Reddit’s marketing measurement, influencing senior leadership and defining how we value our brand and performance efforts. Responsibilities: - Set Long-Term Marketing Strategy: Define the 2–3 year technical roadmap for marketing measurement. Establish the "North Star" metrics and frameworks that determine how Reddit allocates hundreds of millions in marketing budget. - Optimize Marketing ROI: Build and refine Media Mix Models (MMM) and Multi-Touch Attribution (MTA) systems to mathematically quantify the incremental impact of marketing spend. - Bridge B2B & B2C Growth: Design unified frameworks to optimize marketing aimed at both new advertisers (driving revenue) and new users (driving engagement), identifying synergies where brand awareness for one fuels growth for the other. - Advance Causal Inference & Experimentation: Lead the design of complex "always-on" incrementality testing and geo-holdout experiments. Develop methodologies to measure the long-term "halo effect" of brand marketing on organic growth. - Lead Through Influence: Collaborate deeply with Marketing, Growth, a

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Job Duties: Design, develop, and train advanced machine learning models, including deep neural networks, transformer-based architectures, and reinforcement learning systems, to power large-scale online advertising ranking and optimization platforms. Lead the development and optimization of complex feature representations, including high-dimensional embeddings, contextual and temporal signals, and cross-session user behavior modeling. Drive end-to-end model lifecycle execution, including system architecture design, large-scale experimentation, model deployment, performance monitoring, and iterative infrastructure improvements in production environments. Collaborate closely with product, data, and infrastructure engineering teams to translate business objectives into scalable, statistically rigorous modeling solutions. Conduct advanced experiment design and causal analysis to evaluate model impact and inform strategic decisions. Provide technical leadership and mentorship to machine learning engineers and contribute to organization-wide modeling standards, best practices, and long-term technical strategy. Shape the long-term modeling vision across multiple advertising domains, including conversion optimization, application advertising, shopping, and brand advertising. Full-time telecommuting is an option. Requirements: Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline and (3) three years of experience in the job offered or related occupation. Special Skill Requirements: 1) Python, Java, and Scala; 2) C++, Go, or Rust; 3) major machine learning frameworks and libraries; 4) applied statistics, hypothesis testing and experiment design for online machine learning systems; 5) large-scale data processing and analytics frameworks; 6) deployment and operation of production systems in containerized and distributed environments; 7) Designing and training advanced models, including deep neural networks, transformer-based architectures, and reinforcement learning models; 8) marketplace dynamics, such as real-time bidding (RTB) or pacing control systems; 9) developing and optimizing online advertising systems, including ad ranking, targeting, and market place; 10) providing technical leadership, mentorship, or guidance to other machine learning engineers. Any suitable combination of education, training and/or experience is acceptable. Full

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. Reddit's relevance challenges are uniquely complex. Our platform is a deeply interconnected network of communities, contributors, and consumers - where the notion of "relevance" spans personalized content ranking, community discovery, and search across an enormous corpus of authentic, user-generated content. We need a senior technical leader who thrives on these hard problems and can raise the bar for how we measure, evaluate, and improve the quality of recommendations and search results across the entire Consumer organization. As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on relevance measurement and evaluation, partnering closely with Feeds and Search ML teams to tackle the most complex ranking, recommendation, and retrieval challenges across Consumer. You will shape how Reddit understands content quality, define the metrics and analytical frameworks that guide relevance improvements, and influence product strategy through rigorous analysis and experimentation. Responsibilities - Serve as the technical authority on relevance metrics and evaluation methodology across Consumer, setting standards for how we measure the quality of feeds, search results, and recommendations in a complex, community-driven environment - Develop metrics frameworks and offline evaluation approaches for ranking and recommendation systems, including proxy metrics that reliably predict long-term outcomes like retention, community health, and user satisfaction - Design and analyze experiments for relevance features, accounting for challenges unique to networked p

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: - Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. - Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. - Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS. - Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph. - Lead Through Cross-Functional and Technical Influence: Collaborate deeply with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution. Set a high technical bar by mentoring others and championing best practices across modeling, experimentation, and measurement. Qualifications: Required: - Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research - For M.S. holders: 10+ years of industry experience in applied science or data science roles - For Ph.D. holders: 6+ years of industry experience in applied science or data science roles - Deep understanding of the ads ecosystem - Demonstrated expertise in at least one of the following areas:&l

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Embedding Machine Learning Platform team is at the forefront of building highly expressive machine learning models that power Reddit’s recommendation systems. We go beyond standard retrieval and ranking architectures, leveraging modern deep learning approaches and scalable model designs to enhance personalization across Reddit’s ecosystem. Our work impacts content discovery, user engagement, and platform growth at a massive scale. How You'll Have Impact As a Staff Machine Learning Engineer , you will own the technical direction for large-scale machine learning models, guiding the development of advanced deep learning architectures and high-impact ML systems. You will partner with leadership to define ML roadmaps, drive innovation in scalable model design and training approaches, and ensure efficient, reliable deployment of ML models in production. This role offers an opportunity to influence key AI-driven systems across Reddit while mentoring and uplifting the team’s technical capabilities. What You’ll Do - Architect and lead the development of next-generation, large-scale machine learning techniques. - Define and execute the ML strategy, identifying opportunities to enhance personalization and recommendation quality across Reddit. - Lead research initiatives on scalable machine learning systems and real-time model adaptation, bringing cutting-edge advancements into production. - Partner with ML infrastructure teams to build high-performance, distributed training systems that efficiently scale across multiple GPUs and cloud environments. - Establish and optimize real-time serving architectures for large-scale embeddings, ensuring low-latency inference and high throughput. - Collaborate cross-functionally with teams in Feed Ranking, Ads, Content Understanding, and Core ML to integrate ML models into Reddit’s key AI-driven systems. - Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing. - Stay at the forefront of AI research, evaluating and introducing new modeling paradigms to keep Reddit’s ML ecosystem cutting-edge. - Drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making. Who You Might Be: - 8+ years of experience in machine learning engineering, with a strong focus on large-scale ML systems and recommendation or personalization systems.&l

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be. Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. About the Ads Data Science Team: The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling. About the Role: Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: - Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. - Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. - Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling te

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence. Ads Content Understanding (ACU) owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for: - The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources). - Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics. - Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations. - Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs. - Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams. We are looking for a Senior Machine Learning Engineer (IC4) who will act as a key contributor to the Content Understanding roadmap for the Monetization org. This is not a research scientist or pure DS role; success is defined by robust, shipped systems and monetization impact. The ideal candidate is a pragmatic engineer with strong software engineering fundamentals and solid ML intuition—not a pure research scientist. This is an Applied MLE role, requiring someone who can evaluate when to leverage hosted LLMs versus custom models, help scale content understanding to new modalities (e.g., video), and drive practical ML solutions that deliver business impact. Responsibilities: - Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable ML pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production. - Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, design reviews, setting technical standards, and uplifting the team’s modeling and systems craft. - Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices.&n

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. As a Staff Data Scientist on the team, you will play an influential role in guiding product strategy through proactively identifying opportunities, conducting exploratory analyses and sharing insights, and driving learning through experimentation. Responsibilities: - Help build the long term product strategy by identifying opportunities to attract new users, increase engagement, and drive retention - Influence strategic roadmaps through data-driven insights into user behaviors and needs - Design metrics that help evaluate the health of the business and the success of our products, including any ETL development needed for consistent and robust analysis - Drive experimentation from design through execution and analysis to maximize learnings and guide future investment decisions - Build self-serve tools for product and engineering partners that answer common questions and/or increase data literacy in the organization - Work cross functionally with product, engineering, and design teams to ensure insights make it to the product - Scale your work to other parts of the data organization through mentoring more junior data scientists, improving processes, and providing perspective on the most important problems Required Qualifications: - Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research - For M.S. holders: 10+ years of industry experience in applied science or data science roles - For Ph.D. holders: 6+ years of industry experience in applied science or data science roles - Expert knowledge of SQL and relational databases - Familiarity with statistical analysis and the preferred programming languages of the team (R / Python) - Demonstrated ability to influence and guide product strategy with data - Demonstrated ability to take ambiguous problems and solve them in a structured, h

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, ML Ranking Platform is the brain behind how millions of people discover content every day. ML Ranking Platform powers 40+ Reddit products including home feed, search, subreddit feeds, push notifications and others. It runs a scatter-gather ranking orchestration service that coordinates contextualized and personalized ranking on Reddit. We provide Product Engineers and ML Modeling Engineers with a platform to develop the ranking, recommendation and personalization products to delight, engage and retain Reddit users. How You'll Have Impact As a Senior Software Engineer, ML Ranking Platform , you will design, implement and maintain highly robust, scalable, reliable and performant ranking systems that power personalized feeds, search, and other products at Reddit scale. You’ll drive and deliver high-impact projects, building the ranking engines that orchestrate workflows for a reliable and performant ML-based system. Your work not only powers Reddit feeds; it’ll also shape how communities connect, grow, and thrive across Reddit! - Design and implement the next generation ML ranking system that powers the personalized feeds, search and other products at Reddit - Design and develop ML and Generative AI systems in cloud-based production environments at scale - Partner closely with Product, Infrastructure and Engineering teams and translate requirements into scalable ML systems - Write efficient, scalable and maintainable code that will help us iterate quickly and safely - Champion and drive engineering processes and best practices - Raise the bar for engineering across the team through code reviews, mentorship and knowledge sharing Who You Might Have: - 5+ years of experience as a software engineer developing large-scale distributed systems and data intensive ML based system, using Go, Python, C++ or any object oriented programming language - 5+ years of experience with designing and implementing large-scale performant and reliable machine learning systems. Experience with recommendation systems is preferred. - Experience with developing and improving tools such as deployment, automation, system diagnosis, ML monitoring etc. - Strong organizational skills with the ability to prioritize tasks and keep projects on schedule with a strong attention to detail - BS degree in Computer Science, a similar technical field of study or equivalent practical experience - Fa

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We’re looking for a Senior Staff Machine Learning Engineer to lead Reddit’s next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform. This role requires deep expertise in mainstream ML user modeling approaches (e.g., large-scale embeddings, user interest modeling, affinities, behavioral signals) and the ability to reimagine these systems in the GenAI era—leveraging LLMs and foundation models to unlock step-change improvements in fidelity, adaptability, and expressiveness. You will set the technical direction for this space, leading the design and implementation of Reddit’s core user representation layer—spanning embeddings, interest modeling, and key user attributes. You’ll ensure this foundation is scalable, reliable, and widely adopted across Feeds, Search, Notifications, and Ads, partnering closely with product, infrastructure, and downstream ML teams to drive measurable impact. This is a high-impact role. The systems you build will shape how hundreds of millions of people experience Reddit every day—what they see, what they discover, and the communities they connect with. Your work will directly advance personalization and relevance at global scale, strengthening Reddit as a platform for meaningful connection and belonging. What you'll do: - Design User Understanding Strategy: Define a unified user understanding framework and strategy: how users are represented (embeddings, tags, attributes, LLM-based user profile), how they are computed, stored, and exposed. Provide thought leadership in user understanding and user modeling by setting a long-term technical vision and advancing the state-of-the-art in the field. - Build Foundational User Models: Lead design and implementation of advanced user models, e.g. large-scale user representation learning (sequence-based, multi-interest, multi-task) that share representations across surfaces to improve personalization experience across key Reddit products e.g. Feeds, Notification, Search and Ads, balancing latency, cost, and performance. - Reimagine user understanding with LLM/Gen-AI: Evolve user modeling beyond traditional representations by leveraging LLMs to build richer user understanding (e.g., dynamic user profiles, intent inference, semantic reasoning over user behavior). Explore how LLMs can augment or unify embeddings, attributes, and taxonomies to enable more adaptive, interpretable, and context-aware personalization. - Ship Large Scale User Understanding as a System: Partner with platform teams to design and build core components for large-scale l

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Ads Content Understanding (ACU) is Reddit’s core commercial content understanding team for Ads. The team owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for: - The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources). - Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics. - Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations. - Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs. - Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams. We are looking for a Staff Machine Learning Engineer who will lead the Commercial Content Understanding roadmap for the Monetization org and act as the technical owner for ACU’s signals and ML systems. Roughly 50% of their time should be spent in technical leadership and mentorship (driving designs, standards, cross-team alignment), and 50% in direct hands-on work (modeling, pipelines, and debugging complex production systems). Responsibilities: - Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, acting as de facto tech lead for content understanding and signals: driving design reviews, setting technical standards, and uplifting the team’s modeling and systems craft. - Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices. - Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost) - Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products. - Lead design and implementation of signals pipelines and produce an ACU signals registry. Partner with platform teams and other content understanding teams to ensure ef

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. Reddit's experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization. As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most complex and high-stakes experimentation challenges across Consumer. You will shape how Reddit learns from its experiments, ensure we draw valid causal conclusions in the presence of network effects and interference, and influence product strategy through rigorous experimental design and analysis. Responsibilities: - Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment - Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation - Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches - Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit's Ads Data Science team is seeking a highly motivated Principal Data Scientist to drive the strategic application of advanced quantitative methods across our advertising platform to advance the intelligence powering the advertiser experience on Reddit. In this pivotal leadership role, you will be responsible for defining and implementing the next generation of foundational data science solutions, leveraging expertise in statistics, econometrics, machine learning and/or other quantitative methods to optimize Reddit's Ads marketplace. You will partner closely with Analytics Engineering to ensure our underlying data systems are continuously upleveled to support advanced analysis and modeling at scale. You will be a strategic partner, collaborating closely with Product, Engineering, and Business leaders to establish the long-term vision for measurement, prediction, and optimization. As a thought leader, you will champion scientific rigor, causal inference, and economic modeling, while providing deep mentorship to the broader team. If you are passionate about applying foundational quantitative science to solve complex, high-impact business problems, join us in shaping the future of Reddit ads. What you’ll do - Define the future of Ads Data Science: Own the design and long-term evolution of our core Ads Data Science solutions and infrastructure, building for the next several years of continued scale, revenue growth, and relevance. - Strategic leadership & scientific roadmap: Identify fundamental gaps and opportunities in our current systems (including platform, auction, targeting, and full-funnel relevance models). Lead the strategic design and scientific roadmap for new solutions to significantly improve Advertiser ROI, User experience, and Reddit revenue. - Drive end-to-end impact: Take end-to-end ownership of complex problem domains such as full funnel acceleration, advertiser lifetime value (LTV), and developing advanced predictive and causal frameworks that power Reddit’s strategic investments. - Establish scientific standards: Define and codify best practices for large-scale statistical modeling, economic analysis, causal inference, offline model evaluation, and A/B experimentation to ensure scientific rigor and trust across the Ads data science and engineering teams. - Technical deep dive & authority: Be the undisputed domain authority for data scientists, engineers, and product managers on complex problems involving large-scale

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. Team Overview We’re building a scalable feature platform that powers Ads ML by making high-quality features and training datasets easy to build, share, and maintain. Our small but growing team works on projects like batch & realtime feature management platform, training set generation platform, sequence features platform and, agentic and automated ML workflows for feature lifecycle management. We are looking for an engineer with experience in building high-scale data infrastructure and exposure to ML platforms to help evolve and scale our feature management systems. This is not a pure ML modeling role. The ideal candidate is excited about building reliable infrastructure, data pipelines, and developer-facing tools that make ML engineers more productive. What You’ll Do - Design and build data infrastructure that supports large-scale feature and training set computation, transformation, and storage. - Develop frameworks for batch and real-time features with a focus on reliability, scalability, and ease of use. - Build platform capabilities for feature governance, including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning - Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems. - Build systems that support agentic ML workflows, including automated feature discovery, feature quality evaluation and feature lifecycle management - Contribute to operational excellence through observability, performance tuning, reliability engineering, and cost optimization initiatives. What You Bring - 3+ years in data infrastructure/platform engineering or ML infrastructure platforms. - Hands-on experience building production services, data pipelines, APIs, workflow systems, or developer tools. - Experience with at least one distributed data or compute system such as Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery, or similar technologies. - Familiarity with ML data workflows such as feature generation, training dataset creation, batch processing, real-time data processing, model training, experimentation, or online serving. - Strong coding skills and ability to

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. Reddit's experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization. As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most complex and high-stakes experimentation challenges across Consumer. You will shape how Reddit learns from its experiments, ensure we draw valid causal conclusions in the presence of network effects and interference, and influence product strategy through rigorous experimental design and analysis. Responsibilities: - Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment - Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation - Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches - Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit. - Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more - Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration - Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment - Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more - Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges Who You Might Be: - 5+ years of experience in ML infrastructure, including model training and model deployments - Hands-on experience with ML optimization, including memory and GPU profiling - Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more - Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb) - Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc. - Deep experience working with distributed training frameworks, including Ray and Kubernetes - Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle. - Strong organizational & communication skills - Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus</li

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We are hiring Machine Learning Engineers across our Consumer Engineering organization, giving you the opportunity to work on a wide range of high-impact problems across the Consumer ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On We are looking for a Staff Machine Learning Engineer to help drive the next generation of Reddit’s ML ecosystem across recommendations, search, messaging, and foundational AI systems. You will lead high-impact initiatives from ideation to production, shaping both technical strategy and product direction across multiple ML domains. This is a highly cross-functional role partnering with Product, Data Science, and Engineering to deliver meaningful user and business impact. This role sits at the intersection of: - Relevance & recommendation systems (content, search, notifications) - AI-powered discovery & LLM-driven experiences - Content and user understanding & large-scale representation learning - Large-scale ML infrastructure and pipelines What You’ll Do - Lead end-to-end ML initiatives from ideation through production and iteration, shaping technical direction and translating product goals into scalable solutions - Architect, build and deploy large-scale ML systems across recommendation, search, and content/user understanding, including retrieval/ranking models, representation learnings embeddings optimizations, and LLM or GenAI-powered capabilities - Drive measurable impact on user engagement, discovery, and long-term value - Collaborate with cross-functional teams to align product and technical roadmaps and unlock key future ML capabilities - Stay at the forefront of AI research, evaluating and introducing new AI/ML paradigms to keep Reddit’s ML ecosystem at

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. About the Team The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company’s ML ecosystem. Responsibilities - Design and build systems that improve the efficiency of ML training and inference workloads. - Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance. - Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization. - Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements. - Build benchmarking frameworks and performance dashboards for training and serving systems. - Optimize distributed training infrastructure, data pipelines, and model serving architectures. - Lead cross-functional initiatives that improve the productivity of Reddit ML engineers. - Drive technical strategy for ML platform scalability, reliability, and cost efficiency. Qualifications Required - BS, MS, or PhD in Computer Science or a related field. - 5+ years of software engineering experience. - Strong proficiency in Python - Profiency in at least one systems language (Go, C++, Rust, or Java) preferred - Experience building distributed systems at scale. - Experience with machine learning infrastructure, training systems, or model serving platforms. - Deep understanding of performance engineering and systems optimization. - Strong debugging and profiling skills. Preferred - Experience with large-scale recommendation, ranking, generative AI, or foundation model systems. - Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark - Familiarity with GPU architectures and performan

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. Reddit's relevance challenges are uniquely complex. Our platform is a deeply interconnected network of communities, contributors, and consumers - where the notion of "relevance" spans personalized content ranking, community discovery, and search across an enormous corpus of authentic, user-generated content. We need a senior technical leader who thrives on these hard problems and can raise the bar for how we measure, evaluate, and improve the quality of recommendations and search results across the entire Consumer organization. As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on relevance measurement and evaluation, partnering closely with Feeds and Search ML teams to tackle the most complex ranking, recommendation, and retrieval challenges across Consumer. You will shape how Reddit understands content quality, define the metrics and analytical frameworks that guide relevance improvements, and influence product strategy through rigorous analysis and experimentation. Responsibilities - Serve as the technical authority on relevance metrics and evaluation methodology across Consumer, setting standards for how we measure the quality of feeds, search results, and recommendations in a complex, community-driven environment - Develop metrics frameworks and offline evaluation approaches for ranking and recommendation systems, including proxy metrics that reliably predict long-term outcomes like retention, community health, and user satisfaction - Design and analyze experiments for relevance features, accounting for challenges unique to networked p

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: US remote-friendly or any office location - SF, LA, CHI, NY The Data Science Team at Reddit is growing and we are looking for experienced Data Scientists to partner with our cross-functional partners (Product, Engineering, Designer, Marketing, Business Development etc.) to help us build and improve the systems that continuously drive our user and revenue growth. As a Senior Data Scientist on the team, you will have the opportunity to play a significant role in driving the success of key product areas at Reddit (Consumer, Ads, Safety etc.). You will lead and contribute to defining the product strategy through measurement and metrics design, experimentation and causal analyses, supporting product decisions via deep data analyses, and research. This person will be an industry technical leader with a solid technical background, strong business acumen, and excellent cross-functional stakeholders management skills. You will go through a general Data Scientists hiring process and get matched to the product area that best fits your background and interest. Responsibilities: - Develop action-oriented insights to drive the product strategy through observational causal analysis and experiment meta-analysis, and clearly communicate results to stakeholders up to the C-suite to take action based on the recommendations - Uplevel experimentation practices on the team through guiding design, execution, and deep dive analyses to maximize learnings from A/B tests - Create new ETLs, tables, dashboards, and other self-serve tools to enable other data scientists and cross-functional partners to find and interact with data seamlessly - Design, evaluate, and/or measure team-level KPIs to enable quarterly goal setting and demonstrate team impact - Regularly engage with stakeholders to gather feedback and share progress on work at all stages to ensure alignment between DS and other teams on business goals and outcomes - Mentor more junior data scientists and business partners in data science best practices and methods to increase data literacy and improve decision making Required Qualifications: - Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research - For M.S. holders: 5+ years of industry experience in applied science or data science roles - For Ph.D. holders: 4+ years of industry experience in applied science or data

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team Description This role sits in the Ads Optimization organizations, which are responsible for the health and performance of Reddit’s ads marketplace. We focus on: - Designing the auction and bidding mechanisms that decide which ads show to which users and at what price. - Building optimization systems that help advertisers achieve their goals (e.g., conversions, ROAS) under budget and delivery constraints. - Ensuring marketplace quality by improving user experience with ads, fighting ad blindness, and increasing valuable ad opportunities on the platform. You’ll join a set of tight-knit engineers working on high-impact, internet-scale problems at the core of Reddit’s revenue engine, collaborating closely with Product, Data Science, and Infra partners across Reddit Ads. Role Description We are hiring Machine Learning Engineers (IC4) to build and evolve the auction, bidding and budgeting systems that power Reddit Ads. In this role, you will: - Design and implement optimization algorithms for auctions, bidding strategies, and pacing that balance advertiser performance, user experience, and marketplace efficiency. - Own systems end-to-end: from problem formulation and algorithm design to experimentation, production deployment, and ongoing iteration. - Work across Ads Optimization (bid strategies, budget optimization, pacing) to deliver measurable wins for advertisers and Redditors. We are hiring a Senior (IC4) level: - IC4 MLEs lead more complex or multi-quarter initiatives, set technical direction for key parts of the bidding/auction/pacing stack, and mentor other engineers while remaining hands-on. Responsibilities Auction, Bidding, and Pacing Systems - Design and implement models and policies that: - Compute bids for different optimization objectives (e.g., CPC, CPA, ROAS-based strategies). - Pace budgets smoothly over time across accounts, campaigns, and ad groups while preventing overspend or underspend. - Allocate spend and auction participation intelligently across segments, surfaces, and time zones. - Translate product

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Notifications Relevance team at Reddit is building the next generation of notifications focused on delivering the right content to the right user at the right time using the right channel (push notification, email digest and in-app). We are the second largest growth lever at Reddit and a core component to understanding how to delight our current user base and bring new users to discover all that Reddit has to offer. Reddit is home to some of the most valuable and engaging conversations on the internet. As a Staff Machine Learning Engineer on Notifications Relevance , you'll serve as a technical leader for one of Reddit's highest-leverage ML systems, helping millions of users discover relevant content, communities, and conversations every day. You'll drive the strategy, architecture, and execution of large-scale recommendation systems spanning targeting, budget optimization, retrieval, ranking, measurement, and emerging LLM-powered experiences. This role offers the opportunity to shape the future of engagement and retention at Reddit while pushing the boundaries of personalization and machine learning at massive scale. What You’ll Do - Contribute to advancing Reddit's growth by designing and implementing content discovery algorithms that prioritize a seamless and highly personalized user experience. - Deeply understand the Reddit Notifications product and drive the vision for the notifications relevance team. - Enhance core recommendation capabilities, including candidate retrieval, ranking models, and budgeting optimization, while designing and testing new pipeline components. You will also deploy ML models, integrate LLMs, and ensure robust monitoring and smooth product integration throughout the process. - Serve as the primary ML domain expert, deploying state-of-the-art models at scale, driving architectural decisions, and ensuring robust monitoring and smooth product integration across the engineering organization. - Collaborate across disciplines and with ML, Product, Infrastructure, and DS teams at Reddit to find technical solutions to complex challenges Who You Are - 8+ years of industry experience with deep expertise in large-scale recommendation systems, notifications experience preferred. - Proven ability to identify key opportunities, define roadmaps and drive scalable improvement in notifications relevance. - Strong experience in building and deploying large-scale ML models using frameworks such as PyTorch or Tensorflow.</l

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team overview: The Engagement Modeling Team at Reddit focuses on building machine learning models to drive on-platform user engagement with diverse media and content, with a focus on predictive modeling to improve interactions of click-throughs and video view-throughs. This role offers a unique opportunity to shape and scale Reddit’s Ads prediction models, in alignment with our product goals and driving SoTA modeling advancement. This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders. We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S. Responsibilities: - Set Technical Vision and Strategy: Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives. - Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness. - Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence. - Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs. - Innovate in ML Architecture: Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques. Candidate Profile: The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have: - People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth. - Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives. - Drive Technical Execution: Oversee the model development lifecycle from ideati

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence. Ads Content Understanding (ACU) owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for: - The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources). - Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics. - Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations. - Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs. - Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams. We are looking for a Senior Machine Learning Engineer (IC4) who will act as a key contributor to the Content Understanding roadmap for the Monetization org. This is not a research scientist or pure DS role; success is defined by robust, shipped systems and monetization impact. The ideal candidate is a pragmatic engineer with strong software engineering fundamentals and solid ML intuition—not a pure research scientist. This is an Applied MLE role, requiring someone who can evaluate when to leverage hosted LLMs versus custom models, help scale content understanding to new modalities (e.g., video), and drive practical ML solutions that deliver business impact. Responsibilities: - Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable ML pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production. - Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, design reviews, setting technical standards, and uplifting the team’s modeling and systems craft. - Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices.&n

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Search Recommendations & Relevance team at Reddit is building the next generation of search - one that goes beyond “10 blue links” to deliver real answers, perspectives and conversation from the world's largest corpus of human conversation. We power both Reddit Search and our AI-native Search experience, redefining how users discover and interact with information. Redditors produce the most amazing content about every niche topic in the world – this underleveraged data coupled with modern advances in AI systems is presenting a unique opportunity to quickly build a new kind of search engine. As a Senior Staff, you will design and build a large-scale system that powers end-to-end search relevance at scale. You’ll work across multiple areas of the stack, including query understanding, retrieval, ranking, features, measurement, LLM-based answers, RAG etc, partnering deeply with product, org leads, and other XFN to deliver reliable, high quality systems that can help Reddit Search scale to billions of users. What You’ll Do - Contribute to advancing Reddit's Search and Recommendations products by designing AI-driven Search experience prioritizing seamless and delightful user experience. - Deeply understand the Reddit search product and drive the vision for the search relevance team. - Enhance core search retrieval and ranking, design and implement new search engine features, build and scale search indexes, develop and test new pipeline components. You will also deploy ML models, integrate LLMs, and ensure robust monitoring and smooth product integration throughout the process. - Collaborate across disciplines and with ML, Product, Infrastructure, and DS teams at Reddit to find technical solutions to complex challenges. - Mentor and guide senior and staff engineers in the team. - Influence org-wide technical direction and partner closely with senior leadership to shape the long-term roadmap Who You Are - 10+ years of industry experience with deep expertise in large-scale search and recommendation systems. - Proven ability to identify key opportunities, define roadmaps and drive scalable improvement in search relevance. - Strong experience in building and deploying large-scale ML models using frameworks such as PyTorch or Tensorflow. - Experience working with LLM in production, including evaluation, tuning and deployment. &lt

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . About The Role Reddit is a community of communities. It is built on shared interests, passion, and trust and is home to some of the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. Reddit is hiring a Senior Security Engineer, AI Security to help teams build and ship AI-powered products securely. This role combines product security judgment with hands-on engineering to secure the systems, tools, and workflows behind Reddit's AI efforts. You will review AI-powered product designs, threat model LLM and agentic workflows, and build reusable security primitives that make secure AI development easier for teams across Reddit. This is not an MLE role, but you should be comfortable reasoning about how AI systems fail, how agents use tools, and how security controls fit into inference, retrieval, tool-use, and execution paths. The best candidates combine practical application security judgment with strong builder instincts. They can identify risks before launch, then turn repeated findings into guardrails, scanners, registries, sandboxes, libraries, policy checks, or platform controls that scale beyond one product team. What You'll Do - Review and threat model AI-powered product features, LLM integrations, agentic workflows, MCP servers, tools, plugins, retrieval systems, model outputs, and internal AI tools before launch. - Build reusable AI security primitives such as guardrails, scanners, policy checks, tool-use controls, registries, sandboxes, libraries, and workflow-native enforcement points. - Design security tooling that can sit in the inference, retrieval, or execution path to detect and prevent prompt injection, jailbreaks, tool misuse, data leakage, unsafe code generation, and suspicious agent behavior. - Partner with teams building products and platforms with AI to define practical security controls that fit how they design, build, and ship. - Proactively find, fix, and prevent AI security issues, while making any required product or engineering changes clear and low-friction for partner teams. - Turn one-off AI security issues into systemic fixes, paved paths, measurable controls, and reusable guidance. What We're Looking For - 5+ years of experience in product security, application security, software security, security engineering, backend engineering, or security platform engineering. - Strong application sec

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, ML Ranking Platform is the brain behind how millions of people discover content every day. ML Ranking Platform powers 40+ Reddit products including home feed, search, subreddit feeds, push notifications and others. It runs a scatter-gather ranking orchestration service that coordinates contextualized and personalized ranking on Reddit. We provide Product Engineers and ML Modeling Engineers with a platform to develop the ranking, recommendation and personalization products to delight, engage and retain Reddit users. How You'll Have Impact As a Senior Software Engineer, ML Ranking Platform , you will design, implement and maintain highly robust, scalable, reliable and performant ranking systems that power personalized feeds, search, and other products at Reddit scale. You’ll drive and deliver high-impact projects, building the ranking engines that orchestrate workflows for a reliable and performant ML-based system. Your work not only powers Reddit feeds; it’ll also shape how communities connect, grow, and thrive across Reddit! - Design and implement the next generation ML ranking system that powers the personalized feeds, search and other products at Reddit - Design and develop ML and Generative AI systems in cloud-based production environments at scale - Partner closely with Product, Infrastructure and Engineering teams and translate requirements into scalable ML systems - Write efficient, scalable and maintainable code that will help us iterate quickly and safely - Champion and drive engineering processes and best practices - Raise the bar for engineering across the team through code reviews, mentorship and knowledge sharing Who You Might Have: - 5+ years of experience as a software engineer developing large-scale distributed systems and data intensive ML based system, using Go, Python, C++ or any object oriented programming language - 5+ years of experience with designing and implementing large-scale performant and reliable machine learning systems. Experience with recommendation systems is preferred. - Experience with developing and improving tools such as deployment, automation, system diagnosis, ML monitoring etc. - Strong organizational skills with the ability to prioritize tasks and keep projects on schedule with a strong attention to detail - BS degree in Computer Science, a similar technical field of study or equivalent practical experience - Fa

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Embedding Machine Learning Platform team is at the forefront of building highly expressive machine learning models that power Reddit’s recommendation systems. We go beyond standard retrieval and ranking architectures, leveraging modern deep learning approaches and scalable model designs to enhance personalization across Reddit’s ecosystem. Our work impacts content discovery, user engagement, and platform growth at a massive scale. How You'll Have Impact As a Staff Machine Learning Engineer , you will own the technical direction for large-scale machine learning models, guiding the development of advanced deep learning architectures and high-impact ML systems. You will partner with leadership to define ML roadmaps, drive innovation in scalable model design and training approaches, and ensure efficient, reliable deployment of ML models in production. This role offers an opportunity to influence key AI-driven systems across Reddit while mentoring and uplifting the team’s technical capabilities. What You’ll Do - Architect and lead the development of next-generation, large-scale machine learning techniques. - Define and execute the ML strategy, identifying opportunities to enhance personalization and recommendation quality across Reddit. - Lead research initiatives on scalable machine learning systems and real-time model adaptation, bringing cutting-edge advancements into production. - Partner with ML infrastructure teams to build high-performance, distributed training systems that efficiently scale across multiple GPUs and cloud environments. - Establish and optimize real-time serving architectures for large-scale embeddings, ensuring low-latency inference and high throughput. - Collaborate cross-functionally with teams in Feed Ranking, Ads, Content Understanding, and Core ML to integrate ML models into Reddit’s key AI-driven systems. - Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing. - Stay at the forefront of AI research, evaluating and introducing new modeling paradigms to keep Reddit’s ML ecosystem cutting-edge. - Drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making. Who You Might Be: - 8+ years of experience in machine learning engineering, with a strong focus on large-scale ML systems and recommendation or personalization systems.&l

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Notifications Relevance Team focuses on delivering the right content to the right user at the right time through push, email, and in-app notifications. Our systems and algorithms operate on the world's largest corpus of human conversation, connecting Redditors with what matters - whether it’s recommending similar posts and subreddits, surfacing conversations they’ll care about, or introducing communities they didn’t know they needed. We are looking for an Engineering Manager to lead our Notifications Relevance team, shaping the future of Notifications at Reddit. In this role, you will lead a team of machine learning engineers dedicated to advancing our current Notifications Relevance systems. This is a high-impact team driving DAU growth and long-term user retention by connecting users to what matters most to them. If applying ML / AI in production to improve the relevance of Reddit Notifications excites you, then you’ve found the right place. What You’ll Do - Lead the team that architects and designs notifications relevance at Reddit. - Guide team on holistic, adaptive systems covering budgeting optimization, candidate retrieval, and ranking. - Work with ML engineers to design, implement, and optimize machine-learning models that drive personalization and user re-engagement. - Participate in the full development cycle: design, develop, QA, experiment, analyze, and deploy. - Build and maintain a diverse team that can collaborate across disciplines to find technical solutions to complex challenges. - Serve as a thought partner to product and upper management to ensure your team’s plans align with company goals. - Communicate your team’s work and set expectations with cross-functional stakeholders. - Help your engineers identify career goals and create development plans to achieve them. - Constantly seek opportunities to push your engineers & managers outside their comfort zone and turn followers into leaders. You Have: - 2+ years of experience building and managing engineering teams. - 5+ years of experience as a Machine Learning Engineer or Software Engineer working on large-scale machine learning systems. - Deep understanding of building and deploying large-scale recommender systems (retrieval + ranking) in production. - Hands-on experience working with deep learning models, sequential features and real-time systems. - Experience with distributed t

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Staff Software Engineer, you will help define and lead the vision for Reddit’s large-scale GenAI Platform, shaping the strategy, architecture, and operating model that enable teams across the company to build, deploy, and scale generative AI products with confidence. Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability. - Lead and execute the vision, strategy, and roadmap for Reddit’s large-scale GenAI Platform. - Define the platform architecture and operating model that enable teams to build, deploy, and scale GenAI products reliably. - Drive the strategy for a unified LAG Gateway supporting internally and externally hosted LLMs through consistent APIs and abstractions. - Set the direction for core platform capabilities such as rate and token limit management, intelligent failover, and production resilience. - Shape Reddit’s approach to an enterprise-grade RAG system - Establish the strategic direction for agentic AI workflows and tool-use patterns across the platform. - Own the end-to-end platform strategy from concept through production adoption and long-term evolution. - Drive MLOps and LLMOps standards across CI/CD, testing, versioning, evaluation, and lifecycle management. - Define best practices for observability, monitoring, governance, and operational excellence across GenAI systems. - Partner across engineering, product, and leadership to align platform investments with company priorities and user needs. - Champion platform thinking with a strong focus on scalability, reliability, performance, and developer experience. - Influence technical direction across teams by turning emerging AI capabilities into a scalable platform strategy. Who You Might Be: - 10+ years of experience in ML Engineering, AI Platform Engineering,

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s lower funnel business is rapidly growing and pushing the heavy ranking web conversion models towards state-of-the-art is critical for continued growth. The Conversion modeling Team plays a pivotal role in developing and maintaining machine learning models that drive user conversions from Reddit Ads, with a special focus on predictive modeling around interactions like purchase, signup, add to cart, and other lower funnel user actions. As we expand our machine learning infrastructure and incorporate new engagement signals, we are looking for a skilled Engineering Manager who can lead this critical team. This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders. We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S. Target Skills and Expertise The Engineering Manager (EM) will be responsible for defining the team’s vision, setting strategic direction, and executing a technical roadmap for conversion modeling at Reddit. This involves: - Model Architectures: Expertise in architecting and implementing deep learning models, with experience in ranking, recommendation, or conversion modeling. - ML Frameworks: Proficiency with mainstream ML libraries (TensorFlow, PyTorch). - End-to-End ML Lifecycle: Experience in training, testing, and deploying production-grade machine learning models. - Data Pipelines: Experience orchestrating large-scale data generation and processing pipelines. - Ads domain Experience: Experience in interaction of ranking model with rest of Ads systems like bidding, auction, retrieval etc - Ads Modeling (Preferred): Background in ads modeling or familiarity with engagement prediction models in the ads domain is beneficial. Role responsibilities: The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have: - People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth. - Set Technical Vision and Strategy: Abilit

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. Reddit's relevance challenges are uniquely complex. Our platform is a deeply interconnected network of communities, contributors, and consumers - where the notion of "relevance" spans personalized content ranking, community discovery, and search across an enormous corpus of authentic, user-generated content. We need a senior technical leader who thrives on these hard problems and can raise the bar for how we measure, evaluate, and improve the quality of recommendations and search results across the entire Consumer organization. As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on relevance measurement and evaluation, partnering closely with Feeds and Search ML teams to tackle the most complex ranking, recommendation, and retrieval challenges across Consumer. You will shape how Reddit understands content quality, define the metrics and analytical frameworks that guide relevance improvements, and influence product strategy through rigorous analysis and experimentation. Responsibilities - Serve as the technical authority on relevance metrics and evaluation methodology across Consumer, setting standards for how we measure the quality of feeds, search results, and recommendations in a complex, community-driven environment - Develop metrics frameworks and offline evaluation approaches for ranking and recommendation systems, including proxy metrics that reliably predict long-term outcomes like retention, community health, and user satisfaction - Design and analyze experiments for relevance features, accounting for challenges unique to networked p

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: At Reddit we continue to grow our teams with the best talent. We're completely remote friendly . Team Description: The Marketing Science team at Reddit leverages data to maximize the impact of Reddit’s own marketing investments. We serve as the engine behind our growth, using advanced experimentation, causal inference, and econometrics to understand what drives users to Reddit and what brings advertisers to our platform. We work at the intersection of brand building and performance marketing, ensuring every dollar spent is an investment in the long-term health of our ecosystem. Role Description: Reddit is looking for a highly experienced Staff Data Scientist to lead the strategy and technical execution of our Marketing Intelligence efforts. In this role, you will be the primary architect of how we measure and optimize Reddit’s marketing spend. You will focus on two critical flywheels: B2B Marketing (acquiring and retaining advertisers) and B2C Growth (acquiring and engaging new Redditors). This is a high-autonomy, high-impact role where you will set the long-term strategic goals for Reddit’s marketing measurement, influencing senior leadership and defining how we value our brand and performance efforts. Responsibilities: - Set Long-Term Marketing Strategy: Define the 2–3 year technical roadmap for marketing measurement. Establish the "North Star" metrics and frameworks that determine how Reddit allocates hundreds of millions in marketing budget. - Optimize Marketing ROI: Build and refine Media Mix Models (MMM) and Multi-Touch Attribution (MTA) systems to mathematically quantify the incremental impact of marketing spend. - Bridge B2B & B2C Growth: Design unified frameworks to optimize marketing aimed at both new advertisers (driving revenue) and new users (driving engagement), identifying synergies where brand awareness for one fuels growth for the other. - Advance Causal Inference & Experimentation: Lead the design of complex "always-on" incrementality testing and geo-holdout experiments. Develop methodologies to measure the long-term "halo effect" of brand marketing on organic growth. - Lead Through Influence: Collaborate deeply with Marketing, Growth, a

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic. Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. About the Ads Data Science Team: The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling. About the Role: We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit. Responsibilities: - Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform - Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform - Collaborate with product managers and engineers to define product requirements and translate them into data science solutions - Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition - Communicate findings and recommendations to stakeholders across the organization - Stay up-to-date on the latest advancements in machine learning and data science - Mentor

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Benefits: - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Comprehensive Medical Benefits & Health Care Spending Account - Registered Retirement Savings Plan with matching contributions - Income Replacement Programs - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave LI-Remote #LI-NH1 In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . <span style="font-

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Staff ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit. - Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more - Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration - Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment - Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more - Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges Who You Might Be: - 8+ years of experience in ML infrastructure, including model training and model deployments - Hands-on experience with ML optimization, including memory and GPU profiling - Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more - Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb) - Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc. - Deep experience working with distributed training frameworks, including Ray and Kubernetes - Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle. - Strong organizational & communication skills - Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus</li&

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: US remote-friendly Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic. Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. About the Ads Data Science Team: The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling. About the Role: We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit. Responsibilities: - Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform - Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform - Collaborate with product managers and engineers to define product requirements and translate them into data science solutions - Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition - Communicate findings and recommendations to stakeholders across the organization - Stay up-to-date on the latest

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. Reddit's experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization. As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most complex and high-stakes experimentation challenges across Consumer. You will shape how Reddit learns from its experiments, ensure we draw valid causal conclusions in the presence of network effects and interference, and influence product strategy through rigorous experimental design and analysis. Responsibilities: - Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment - Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation - Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches - Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: - Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities - Intelligent advertising systems including ranking, bidding, measurement, and optimization - Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals - Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems - Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. What You’ll Do - Design, build, and deploy production-grade machine learning models and systems at scale - Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring - Build scalable data and model pipelines with strong reliability, observability, and automated retraining - Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. - Partner cross-func

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. Team Overview We’re building a scalable feature platform that powers Ads ML by making high-quality features and training datasets easy to build, share, and maintain. Our small but growing team works on projects like batch & realtime feature management platform, training set generation platform, sequence features platform and, agentic and automated ML workflows for feature lifecycle management. We are looking for an engineer with experience in building high-scale data infrastructure and exposure to ML platforms to help evolve and scale our feature management systems. This is not a pure ML modeling role. The ideal candidate is excited about building reliable infrastructure, data pipelines, and developer-facing tools that make ML engineers more productive. What You’ll Do - Design and build data infrastructure that supports large-scale feature and training set computation, transformation, and storage. - Develop frameworks for batch and real-time features with a focus on reliability, scalability, and ease of use. - Build platform capabilities for feature governance, including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning - Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems. - Build systems that support agentic ML workflows, including automated feature discovery, feature quality evaluation and feature lifecycle management - Contribute to operational excellence through observability, performance tuning, reliability engineering, and cost optimization initiatives. What You Bring - 3+ years in data infrastructure/platform engineering or ML infrastructure platforms. - Hands-on experience building production services, data pipelines, APIs, workflow systems, or developer tools. - Experience with at least one distributed data or compute system such as Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery, or similar technologies. - Familiarity with ML data workflows such as feature generation, training dataset creation, batch processing, real-time data processing, model training, experimentation, or online serving. - Strong coding skills and ability to

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City & Chicago) our doors are open for you to come into the office as often as you'd like. We’re looking for a Director of Machine Learning to lead Reddit’s efforts in building industry-leading ML systems that keep our platform safe and foster healthy online communities. This leader will drive the strategy, development, and deployment of machine learning models that detect and prevent harmful content and behavior at scale. In this role, you will own the roadmap for Safety and moderation ML, lead a team of applied scientists and engineers, and partner cross-functionally across Product, Engineering, Safety operations, Trust & Community, and AI/ML Platform to innovate on real-time detection, automation, and user protection systems. You will leverage modern ML — including fine-tuned LLMs — to ensure Reddit remains a safe, welcoming, and positive environment for our global user base. Responsibilities - Set the vision and strategy for applying ML to Trust & Safety, ensuring scalable, proactive protection against evolving abuse patterns. - Lead and grow a high-performing Safety ML organization, including applied research, model development, productionization, and continuous improvement. - Develop and deploy cutting-edge Safety ML systems (including fine-tuned LLMs and transformer models) that outperform state-of-the-art solutions in quality, latency, and efficiency. - Partner with Trust & Safety, Product, Moderation, and AI/ML Platform teams to identify safety risks, emerging harm vectors, and ML opportunities that improve detection, enforcement, and user experience. - Drive successful experimentation, evaluation, and model lifecycle management, ensuring high precision, recall, explainability, and policy alignment. - Champion ethical and responsible AI practices in all Safety ML solutions. - Track performance through metrics, research-based iteration, and alignment with Reddit’s safety policies and regulatory standards. - Represent Safety ML leadership internally and externally — including conferences, publications, industry groups, and cross-company collaboration initiatives. Required Qualifications <li&

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. The Ads Foundational Representations (AFR) team develops signals and representations of Reddit’s core entities (ads, posts, users, and so on), capturing the semantic, contextual, and behavioral information that Reddit Ads needs. We work on building embeddings to understand content and users' interests based on the content they engage with. Our team has the potential to highlight one of Reddit's biggest differentiators: genuinely curated, high-quality, extremely relevant, and daily updated organic content. We are a Machine Learning/Data heavy team with a focus on the following areas: - Multimodal & Content Embeddings - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) text and media content by embedding them into a shared space. - Contextual and Behavioral Relevance - Working with Product & Data Science, establishing definitions of what ads are relevant to users and the content we show them next to, building metrics and fine-tuning embeddings to better reflect relevance. - Knowledge Graph Embeddings - Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting & business insights. - User Intent Modeling - Leveraging various techniques to introduce user representations based on the content they interact with: batch & real-time sequence modeling, LLM summarization, etc. - LLM-based Representations - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes The signals and features we create become a key piece in the Ads Delivery funnel, from targeting to the auction, as well as the Business Insights product and other advertiser-facing products such as Creative generation and optimization. As a Senior ML Engineer , you’ll be in charge of the full-cycle execution of ML projects - from collaborating with cross-functional teams on requirements and design, to the implementation of the feature and its experimentation. Responsibilities - Developing new or iterating on existing emb

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team Description: The Ads Marketplace team is a strategic growth engine for Reddit Ads. Our mission is to democratize high-performance advertising by enabling brands to achieve world-class results with minimal friction. To achieve this, we need an incredibly robust, scalable, and state-of-the-art Machine Learning infrastructure. The Ads ML Platform team is at the core of this mission, tasked with building the foundation that powers all of our content understanding, ad targeting, and ad ranking models. We are empowering our ML engineers and data scientists to move faster and build smarter. The Role: As the Staff Product Manager for the Ads ML Platform, you will hold significant ownership over the infrastructure and tools that make our ads marketplace intelligent. You will define the vision and build the roadmap for a platform that enables unparalleled engineering velocity and supports the most modern ML architectures. You will be the bridge between complex ML systems and business outcomes. Whether it's integrating generative AI to increase developer productivity, establishing unified model-serving infrastructure, or optimizing GPU utilization, your work will directly accelerate how quickly and effectively we can ship highly-performant ad products. If you are passionate about the intersection of platform engineering and state-of-the-art ML research, this is the role for you. Responsibilities - Define the Vision: Shape the long-term strategy and roadmap for Reddit’s Ads ML platform, ensuring we are adopting cutting-edge technologies (including Generative AI and LLM workflows) to stay ahead of the curve. - Accelerate Velocity: Build products and tooling that dramatically reduce friction for Machine Learning Engineers (MLEs) and Data Scientists, enabling them to train, deploy, and iterate on models faster than ever. - Cross-Functional Leadership: Partner deeply with Engineering, Data Science, and Ads Product teams to understand their constraints, prioritize platform initiatives, and deliver scalable infrastructure. - Drive Execution and Adoption: Own key performance indicators (KPIs) around platform reliability, latency, cost-efficiency, usage metrics, and developer productivity. - Stay Cutting-Edge: Keep your finger on the pulse of the broader ML ecosystem. Read the latest research papers, understand emerging architectures, and determine how they can be practically a

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence. About the Role Reddit is building a dedicated Ads ML Efficiency function to make model training and inference materially faster, cheaper, safer, and more scalable. As the Engineering Manager for this team, you will lead a group focused on model optimization, training efficiency, GPU enablement, load testing, model performance tooling, and efficiency guardrails across Ads ML. This role sits at the intersection of ML modeling, systems optimization, and organizational leverage. You will partner closely with ranking teams, ML Platform teams and serving owners to identify the highest-value bottlenecks, land measurable efficiency wins, and build the tooling and operating mechanisms that make those wins repeatable. What you’ll do: - Lead & Grow: Hire, mentor, and retain a high-performing team of ML engineers / systems-oriented engineers working on model optimization and ML efficiency. - Set Technical Direction: Define the roadmap for training optimization, inference optimization, launch-readiness tooling, and reusable efficiency primitives across Ads ML. - Deliver Measurable Wins: Drive reductions in model training time, online latency, serving cost, and infra-driven launch risk. - Build Systems and Tooling: Guide the development of profiling, benchmarking, load testing, observability, cost analysis, debugging, and efficiency certification systems. - Operate in the Critical Path: Partner with model owners and platform teams to accelerate high-priority launches and remove bottlenecks from the path to production. - Shape the Team’s Evolution: Balance near-term white-glove optimization work with medium-term platformization and automation. - Build XFN Alignment: Work closely with MLP, AMP, Ranking, and serving teams to clarify boundaries, upstream generic wins, and keep Ads needs on track. - Raise the Bar: Establish engineering rigor around measurement, performance debugging, launch safety, and technical decision-making for efficiency work. What we’re looking for: <li&gt

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. About the Team The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company’s ML ecosystem. Responsibilities - Design and build systems that improve the efficiency of ML training and inference workloads. - Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance. - Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization. - Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements. - Build benchmarking frameworks and performance dashboards for training and serving systems. - Optimize distributed training infrastructure, data pipelines, and model serving architectures. - Lead cross-functional initiatives that improve the productivity of Reddit ML engineers. - Drive technical strategy for ML platform scalability, reliability, and cost efficiency. Qualifications Required - BS, MS, or PhD in Computer Science or a related field. - 5+ years of software engineering experience. - Strong proficiency in Python - Profiency in at least one systems language (Go, C++, Rust, or Java) preferred - Experience building distributed systems at scale. - Experience with machine learning infrastructure, training systems, or model serving platforms. - Deep understanding of performance engineering and systems optimization. - Strong debugging and profiling skills. Preferred - Experience with large-scale recommendation, ranking, generative AI, or foundation model systems. - Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark - Familiarity with GPU architectures and performan

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: - Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities - Intelligent advertising systems including ranking, bidding, measurement, and optimization - Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals - Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems - Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. What You’ll Do - Design, build, and deploy production-grade machine learning models and systems at scale - Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring - Build scalable data and model pipelines with strong reliability, observability, and automated retraining - Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. - Partner cross-func

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: US remote-friendly or any office location - SF, LA, CHI, NY Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. As a Staff Data Scientist on the team, you will play an influential role in guiding product strategy through proactively identifying opportunities, conducting exploratory analyses and sharing insights, and driving learning through experimentation. Responsibilities: - Help build the long term product strategy by identifying opportunities to attract new users, increase engagement, and drive retention - Influence strategic roadmaps through data-driven insights into user behaviors and needs - Design metrics that help evaluate the health of the business and the success of our products, including any ETL development needed for consistent and robust analysis - Drive experimentation from design through execution and analysis to maximize learnings and guide future investment decisions - Build self-serve tools for product and engineering partners that answer common questions and/or increase data literacy in the organization - Work cross functionally with product, engineering, and design teams to ensure insights make it to the product - Scale your work to other parts of the data organization through mentoring more junior data scientists, improving processes, and providing perspective on the most important problems Required Qualifications: - Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research - For M.S. holders: 10+ years of industry experience in applied science or data science roles - For Ph.D. holders: 6+ years of industry experience in applied science or data science roles - Expert knowledge of SQL and relational databases - Familiarity with statistical analysis and the preferred programming languages of the team (R / Python) - Demonstrated ability to influence and guide product str

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. The Ads Foundational Representations (AFR) team develops signals and representations of Reddit’s core entities (ads, posts, users, and so on), capturing the semantic, contextual, and behavioral information that Reddit Ads needs. We work on building embeddings to understand content and users' interests based on the content they engage with. Our team has the potential to highlight one of Reddit's biggest differentiators: genuinely curated, high-quality, extremely relevant, and daily updated organic content. We are a Machine Learning/Data heavy team with a focus on the following areas: - Multimodal & Content Embeddings - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) text and media content by embedding them into a shared space. - Contextual and Behavioral Relevance - Working with Product & Data Science, establishing definitions of what ads are relevant to users and the content we show them next to, building metrics and fine-tuning embeddings to better reflect relevance. - Knowledge Graph Embeddings - Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting & business insights. - User Intent Modeling - Leveraging various techniques to introduce user representations based on the content they interact with: batch & real-time sequence modeling, LLM summarization, etc. - LLM-based Representations - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes The signals and features we create become a key piece in the Ads Delivery funnel, from targeting to the auction, as well as the Business Insights product and other advertiser-facing products such as Creative generation and optimization. As a Senior ML Engineer , you’ll be in charge of the full-cycle execution of ML projects - from collaborating with cross-functional teams on requirements and design, to the implementation of the feature and its experimentation. Responsibilities - Developing new or iterating on existing emb

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The GenAI Security team within Reddit’s Security, Privacy, Assurance, and Corporate Engineering organization protects Reddit’s GenAI usage across employee tools, internal agents, and production user-facing systems. Our mission is to secure and protect Reddit’s AI traffic and GenAI adoption by default. We are building zero-trust, defense-in-depth systems that verify identity, permissions, data access, and semantic intent across AI workflows. A core part of this work is developing practical, high-quality ML models that detect and prevent security risks such as prompt injection, jailbreak attempts, sensitive data exfiltration, unsafe model behavior, anomalous usage, and unauthorized agent actions. We are looking for a Senior Machine Learning Engineer to lead model development for GenAI Security and help establish strong ML practices across SPACE. This role owns the full machine learning lifecycle: problem definition, data ETL, feature engineering, model training, model evaluation, deployment, experimentation, prediction, monitoring, debugging, and retraining. What You’ll Do - Build and improve security-focused ML models for Reddit’s GenAI traffic, including guardrail models, semantic classifiers, anomaly detection models, and other neural network based security signals. - Own model development end to end: define the security problem, assemble and label datasets, build ETL pipelines, engineer features, train models, evaluate quality, deploy to production, monitor performance, and retrain from production feedback. - Use modern deep learning architectures, including neural networks, transformers, sequence models, embeddings, and model distillation where they are the right practical fit. - Design rigorous evaluation suites for adversarial examples, hard negatives, long-context inputs, structured payloads, tool calls, multi-turn workflows, and real production traffic. - Improve model precision, recall, latency, cost, calibration, and operational reliability for high-impact production surfaces. - Build repeatable MLOps workflows for SPACE, including training pipelines, model lineage, artifact management, holdout evaluation, dashboards, rollback paths, and retraining loops. - Partner closely with ML Infrastructure, LLM Gateway, DevX, Ads, Answers, Safety, Privacy, Compliance, and other Security teams to bring security models into real production workflows. - Work pragmatically with Reddit’s evolving ML platform, using existing infrastructure where possible and building focused tooling when needed to keep model iteration moving. - Translate security goals into me

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Ads Content Understanding (ACU) is Reddit’s core commercial content understanding team for Ads. The team owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for: - The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources). - Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics. - Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations. - Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs. - Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams. We are looking for a Staff Machine Learning Engineer who will lead the Commercial Content Understanding roadmap for the Monetization org and act as the technical owner for ACU’s signals and ML systems. Roughly 50% of their time should be spent in technical leadership and mentorship (driving designs, standards, cross-team alignment), and 50% in direct hands-on work (modeling, pipelines, and debugging complex production systems). Responsibilities: - Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, acting as de facto tech lead for content understanding and signals: driving design reviews, setting technical standards, and uplifting the team’s modeling and systems craft. - Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices. - Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost) - Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products. - Lead design and implementation of signals pipelines and produce an ACU signals registry. Partner with platform teams and other content understanding teams to ensure ef

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team The ML Indexing & Retrieval Platform team at Reddit is responsible for building and scaling the core infrastructure that powers machine learning driven recommendations. We design and maintain systems for ML data ingestion, low-latency retrieval services, and end-to-end lifecycle management of data. With a focus on performance, reliability, and scalability, we enable real-time access to high-quality data that supports a wide range of applications, including Content Understanding, Semantic, Lexical retrieval & GenAI applications. How You'll Have Impact You’ll lead the development of next-generation ML Indexing & Retrieval systems, owning the full lifecycle from ideation to production and going beyond incremental improvements to reimagine core platform capabilities. As part of a high-impact, cross-functional team, you’ll solve complex technical challenges to build scalable, reliable platforms that empower developers to efficiently ship critical ML features. Languages: Go, Java, Python, or any object oriented programming language Frameworks: Flink, Airflow, Spark for large scale batch & stream processing Databases: Familiarity with Vector, Lexical & Key-Value Databases Tools: Kubernetes, Docker, AWS, GCP What You’ll Do - Lead the technical strategy, architecture, and implementation of Reddit’s next-generation ML Indexing & Retrieval engine, integrating capabilities across lexical and vector indexing, low-latency retrieval, and emerging GenAI applications. - Partner closely with product engineers across Content Understanding, Search, Feeds, Ads, Growth, and Safety to deliver high-quality experiences. - Define best practices for observability, reliability, and o

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Software Engineer, you will lead the development of a large-scale GenAI Platform at Reddit. - Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability. - Designed and developed ML and Generative AI systems in cloud-based production environments at scale. - Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines. - Implement and operationalize agentic AI workflows with tool use using frameworks such as LangChain and LangGraph. - Drive adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management. - Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production. - Strong ownership mindset and platform thinking. - Ability to lead AI platform delivery from concept to production. Who You Might Be: - 5+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles. - Have experience operating orchestration systems such as Kubernetes at scale - Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more - Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc. - Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders - Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the genAI product development lifecycle. - Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems is a plus &

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Job Duties: Design, develop, and train advanced machine learning models, including deep neural networks, transformer-based architectures, and reinforcement learning systems, to power large-scale online advertising ranking and optimization platforms. Lead the development and optimization of complex feature representations, including high-dimensional embeddings, contextual and temporal signals, and cross-session user behavior modeling. Drive end-to-end model lifecycle execution, including system architecture design, large-scale experimentation, model deployment, performance monitoring, and iterative infrastructure improvements in production environments. Collaborate closely with product, data, and infrastructure engineering teams to translate business objectives into scalable, statistically rigorous modeling solutions. Conduct advanced experiment design and causal analysis to evaluate model impact and inform strategic decisions. Provide technical leadership and mentorship to machine learning engineers and contribute to organization-wide modeling standards, best practices, and long-term technical strategy. Shape the long-term modeling vision across multiple advertising domains, including conversion optimization, application advertising, shopping, and brand advertising. Full-time telecommuting is an option. Requirements: Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline and (3) three years of experience in the job offered or related occupation. Special Skill Requirements: 1) Python, Java, and Scala; 2) C++, Go, or Rust; 3) major machine learning frameworks and libraries; 4) applied statistics, hypothesis testing and experiment design for online machine learning systems; 5) large-scale data processing and analytics frameworks; 6) deployment and operation of production systems in containerized and distributed environments; 7) Designing and training advanced models, including deep neural networks, transformer-based architectures, and reinforcement learning models; 8) marketplace dynamics, such as real-time bidding (RTB) or pacing control systems; 9) developing and optimizing online advertising systems, including ad ranking, targeting, and market place; 10) providing technical leadership, mentorship, or guidance to other machine learning engineers. Any suitable combination of education, training and/or experience is acceptable. Full

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Notifications Relevance team at Reddit is building the next generation of notifications focused on delivering the right content to the right user at the right time using the right channel (push notification, email digest and in-app). We are the second largest growth lever at Reddit and a core component to understanding how to delight our current user base and bring new users to discover all that Reddit has to offer. Redditors produce the most amazing content about every niche topic in the world. Leveraging machine learning and large-scale system development, we process hundreds of millions of posts and user activities to provide personalized recommendations for tens of millions of users. As a Senior Staff, you will design and build a large-scale system that powers end-to-end recommendation systems at scale. You’ll work across multiple areas of the stack, including budget optimization, retrieval, ranking, features, measurement, LLM-based answers, etc, partnering deeply with product, org leads, and other XFN to deliver reliable, high quality systems that can help Reddit Notifications push the boundary on state of the art. What You’ll Do - Contribute to advancing Reddit's growth by designing and implementing content discovery algorithms that prioritize a seamless and highly personalized user experience. - Deeply understand the Reddit Notifications product and drive the vision for the notifications relevance team. - Enhance core recommendation capabilities, including candidate retrieval, ranking models, and budgeting optimization, while designing and testing new pipeline components. You will also deploy ML models, integrate LLMs, and ensure robust monitoring and smooth product integration throughout the process. - Serve as the primary ML domain expert, deploying state-of-the-art models at scale, driving architectural decisions, and ensuring robust monitoring and smooth product integration across the engineering organization. - Collaborate across disciplines and with ML, Product, Infrastructure, and DS teams at Reddit to find technical solutions to complex challenges. - Mentor and guide senior and staff engineers in the team. - Partner closely with senior leadership and cross-functional org leads to shape long-term roadmaps, balancing immediate operational wins with strategic technical objectives. Who You Are - 10+ years of industry experience with deep expertise in large-scale recommendation systems, notifications experience preferred. - Proven

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We’re looking for a Senior Staff Machine Learning Engineer to lead Reddit’s next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform. This role requires deep expertise in mainstream ML user modeling approaches (e.g., large-scale embeddings, user interest modeling, affinities, behavioral signals) and the ability to reimagine these systems in the GenAI era—leveraging LLMs and foundation models to unlock step-change improvements in fidelity, adaptability, and expressiveness. You will set the technical direction for this space, leading the design and implementation of Reddit’s core user representation layer—spanning embeddings, interest modeling, and key user attributes. You’ll ensure this foundation is scalable, reliable, and widely adopted across Feeds, Search, Notifications, and Ads, partnering closely with product, infrastructure, and downstream ML teams to drive measurable impact. This is a high-impact role. The systems you build will shape how hundreds of millions of people experience Reddit every day—what they see, what they discover, and the communities they connect with. Your work will directly advance personalization and relevance at global scale, strengthening Reddit as a platform for meaningful connection and belonging. What you'll do: - Design User Understanding Strategy: Define a unified user understanding framework and strategy: how users are represented (embeddings, tags, attributes, LLM-based user profile), how they are computed, stored, and exposed. Provide thought leadership in user understanding and user modeling by setting a long-term technical vision and advancing the state-of-the-art in the field. - Build Foundational User Models: Lead design and implementation of advanced user models, e.g. large-scale user representation learning (sequence-based, multi-interest, multi-task) that share representations across surfaces to improve personalization experience across key Reddit products e.g. Feeds, Notification, Search and Ads, balancing latency, cost, and performance. - Reimagine user understanding with LLM/Gen-AI: Evolve user modeling beyond traditional representations by leveraging LLMs to build richer user understanding (e.g., dynamic user profiles, intent inference, semantic reasoning over user behavior). Explore how LLMs can augment or unify embeddings, attributes, and taxonomies to enable more adaptive, interpretable, and context-aware personalization. - Ship Large Scale User Understanding as a System: Partner with platform teams to design and build core components for large-scale l

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible first workforce! The Ads Measurement Org is dedicated to enhancing the efficiency and user-friendliness of our advertising platform. The Measurement Modeling team owns all the Machine Learning solutions for Ads Measurement, including Identity Matching, Identity Graph, Utility Enhancement for Ads Privacy, Modeled Conversion, and new Measurement Modeling Initiative. As critical and complex part, in Identity Modeling, we are building new advanced machine learning solutions, the space resides in intersection of ads stack that interacts with various upstream and downstream systems, it serves critical business needs for monetization and consumer as well, including Measurement & Reporting, Experimentation, Personalization, Delivery, and Safety etc, requires major XFN as well as cross team/org collaborations. We are looking for an IC5 Staff ML Engineer of Ads Identity Modeling, to define long term direction and drive architecture evolution, be responsible for engineering quality and enforce best practice, lead new exploration and cross-org collaboration in new modeling initiatives, and champion ML/AI innovation to ensure the solutions utilize SOTA ML technology. Our diverse group of engineers, product managers, data scientists, and ads specialists is excited to welcome you on board! Minimum Qualifications: - 7+ years of professional software engineering experience, with at least 3+ years focused on ML-driven systems at scale - Demonstrated experience architecting and building ads measurement modeling solutions leveraging advanced machine learning techniques - Strong knowledge of various identifiers (cookies, hashed emails, phone numbers, IP addresses, user agents) and their use in identity resolution - Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference - Solid understanding of large-scale data processing, distributed computing, and data infrastructure (e.g., Spark, Kafka, Beam, Flink) - Proven technical leadership in cross-functional settings, driving architectural decisions and influencing stakeholders (product, data science, privacy, legal) - Excellent communication, mentoring, and collaboration skills to align teams on a long-term vision for identity resolution Responsibilities: - Lead the technical strategy and architecture for our company’s ads identity modeling solutions and other related ads measurement models - Design and train advanced ML mod

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: US remote-friendly Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be. Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. About the Ads Data Science Team: The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling. About the Role: Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: - Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. - Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. - Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence Team Overview We are building the next generation of ML research tools and agentic AI platforms that power machine learning development across Reddit. Our mission is to accelerate the Ads ML lifecycle – from experimentation and training to deployment, evaluation, and autonomous operations – through scalable platform services, intelligent automation, and developer-centric tooling. Our team owns critical platform capabilities including offline ML experimentation systems, production training orchestration frameworks, ML lifecycle automation and, agentic ML frameworks that enable faster model iterations. We are looking for an experienced engineer with deep expertise in large-scale distributed systems, ML platforms, and emerging agentic architectures to help define and build the foundational tooling for the next generation of our machine learning devX tooling. What You’ll Do - Design and build large-scale offline ML experimentation platforms that enable reproducible research, model development, evaluation, and promotion workflows. - Develop production-grade training orchestration frameworks supporting distributed training, hyperparameter optimization, model evaluation, and automated retraining. - Build infrastructure for experiment tracking, metadata management, lineage, artifact versioning, model registries, and reproducibility. - Partner with ML engineers and researchers to improve experimentation velocity and operational efficiency. - Build automated workflows for model promotion, rollback, compliance validation, and continuous evaluation. - Design and build an agentic AI execution platform supporting autonomous and human-in-the-loop workflows, including multi-agent orchestration, memory/context systems, and scalable workflow infrastructure. What You Bring - 5+ years in infrastructure/platform engineering or large-scale distributed systems. - 2+ years of hands-on experience building and operating production ML infrastructure, developer SDKs, platform APIs, or self-service AI tooling. - Experience building workflow orchestration systems, developer platforms, or large-scale automation framewor

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: At Reddit we continue to grow our teams with the best talent. We're completely remote friendly . Team Description: The Marketing Science team at Reddit leverages data to maximize the impact of Reddit’s own marketing investments. We serve as the engine behind our growth, using advanced experimentation, causal inference, and econometrics to understand what drives users to Reddit and what brings advertisers to our platform. We work at the intersection of brand building and performance marketing, ensuring every dollar spent is an investment in the long-term health of our ecosystem. Role Description: Reddit is looking for a highly experienced Staff Data Scientist to lead the strategy and technical execution of our Marketing Intelligence efforts. In this role, you will be the primary architect of how we measure and optimize Reddit’s marketing spend. You will focus on two critical flywheels: B2B Marketing (acquiring and retaining advertisers) and B2C Growth (acquiring and engaging new Redditors). This is a high-autonomy, high-impact role where you will set the long-term strategic goals for Reddit’s marketing measurement, influencing senior leadership and defining how we value our brand and performance efforts. Responsibilities: - Set Long-Term Marketing Strategy: Define the 2–3 year technical roadmap for marketing measurement. Establish the "North Star" metrics and frameworks that determine how Reddit allocates hundreds of millions in marketing budget. - Optimize Marketing ROI: Build and refine Media Mix Models (MMM) and Multi-Touch Attribution (MTA) systems to mathematically quantify the incremental impact of marketing spend. - Bridge B2B & B2C Growth: Design unified frameworks to optimize marketing aimed at both new advertisers (driving revenue) and new users (driving engagement), identifying synergies where brand awareness for one fuels growth for the other. - Advance Causal Inference & Experimentation: Lead the design of complex "always-on" incrementality testing and geo-holdout experiments. Develop methodologies to measure the long-term "halo effect" of brand marketing on organic growth. - Lead Through Influence: Collaborate deeply with Marketing, Growth, and Finance to translate complex data insights into actionable budget shifts. - Be the Technical Guide for the Team : Mentor junior scientists and set the technical bar for code quality and statistical rigor across the Marketing organization. Minimum Qualifications: - Education: Advanced degree (Master’s or Ph.D.) in Statistics, Economics, Mathematics, or a related quantitative field. - Experience: - For M.S. holders: 10+ years of industry experience in marketing science, growth data science, or econometrics. - For Ph.D. holders: 6+ years of industry experience. - Domain Expertise: Deep understanding of the marketing ecosystem, including hands-on experience with Marketing Mix Modeling (MMM), Incrementality Testing, and Customer Lifetime Value (LTV) prediction. - Technical Skills: Advanced proficiency in Python or R and SQL. Experience building production-grade data pipelines and using machine learning for predictive modeling (e.g., churn prediction, lead scoring). - Strategic Communication: Proven track record of influencing C-suite stakeholders and "translating" complex statistical concepts into business strategy. - Adaptability: Experience working in fast-paced environments where you must navigate ambiguity and build frameworks from the ground up. Preferred Qualifications: - Experience with Bayesian structural time series or causal inference libraries. - Previous experience in a high-growth marketplace or social media platform. - A passion for the Reddit community and an understanding of our unique "Ads-as-Content" philosophy. Benefits: - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k with Employer Match - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave LI-REMOTE Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $217,000 - $303,900 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. As a Staff Data Scientist on the team, you will play an influential role in guiding product strategy through proactively identifying opportunities, conducting exploratory analyses and sharing insights, and driving learning through experimentation. Responsibilities: - Help build the long term product strategy by identifying opportunities to attract new users, increase engagement, and drive retention - Influence strategic roadmaps through data-driven insights into user behaviors and needs - Design metrics that help evaluate the health of the business and the success of our products, including any ETL development needed for consistent and robust analysis - Drive experimentation from design through execution and analysis to maximize learnings and guide future investment decisions - Build self-serve tools for product and engineering partners that answer common questions and/or increase data literacy in the organization - Work cross functionally with product, engineering, and design teams to ensure insights make it to the product - Scale your work to other parts of the data organization through mentoring more junior data scientists, improving processes, and providing perspective on the most important problems Required Qualifications: - Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research - For M.S. holders: 10+ years of industry experience in applied science or data science roles - For Ph.D. holders: 6+ years of industry experience in applied science or data science roles - Expert knowledge of SQL and relational databases - Familiarity with statistical analysis and the preferred programming languages of the team (R / Python) - Demonstrated ability to influence and guide product strategy with data - Demonstrated ability to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way - Familiarity with causal inference techniques and causal models - Excellent communication and experience working with senior leaders / stakeholders - Entrepreneurial, self-directed, and enthusiastic about solving problems - Demonstrated ability to mentor other data scientists and share best practices to elevate the data science practice at Reddit - Conform in innovative and fast-paced environments, and have a bias toward action. - Can discuss complex topics with technical and non-technical audiences Benefits: - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Comprehensive Medical Benefits & Health Care Spending Account - Registered Retirement Savings Plan with matching contributions - Income Replacement Programs - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave LI-REMOTE In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be. Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. About the Ads Data Science Team: The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling. About the Role: Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: - Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. - Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. - Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS. - Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph. - Lead Through Cross-Functional and Technical Influence: Collaborate deeply with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution. Set a high technical bar by mentoring others and championing best practices across modeling, experimentation, and measurement. Qualifications: - Required: - Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research - For M.S. holders: 10+ years of industry experience in applied science or data science roles - For Ph.D. holders: 6+ years of industry experience in applied science or data science roles - Deep understanding of the ads ecosystem - Demonstrated expertise in at least one of the following areas: - Measurement & Experimentation at Scale (with focus on lift and attribution) - Identity Graph Creation & Resolution Methodology and Infrastructure - Predictive Modeling with Signal Loss - Advanced proficiency in statistical programming (Python or R) and SQL - Experience with machine learning or optimization techniques - Strong understanding of experimental design, causal inference, or A/B testing methodologies - Exceptional problem-solving and communication skills, with a track record of influencing product and engineering partners - Experience working in fast-paced, ambiguous environments with cross-functional teams Benefits: - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Comprehensive Medical Benefits & Health Care Spending Account - Registered Retirement Savings Plan with matching contributions - Income Replacement Programs - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave LI-Remote In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Job Duties: Design, build, and deploy industrial-level machine learning models to solve critical problems in ad ranking, bidding, and optimization. Take full ownership of the ML lifecycle, from ideation and research to building scalable serving systems and maintaining models in production. Perform systematic feature engineering to transform raw, diverse data into high-quality features that drive model performance. Work closely with product managers, data scientists, and engineers to translate business challenges into effective ML solutions. Improve the reliability and stability of our ML systems by building robust monitoring, alerting, and automated retraining pipelines. Research new algorithms, stay up-to-date with state-of-the-art ML techniques, and contribute to the team's strategy and roadmap. Full-time telecommuting is an option. Requirements: Master’s degree in Computer Science, Mathematics, Engineering (any field) or related quantitative discipline and (3) three years of experience in the job offered or related occupation. Special Skill Requirements: 1.) Machine Learning; 2.) TensorFlow; 3.) Python and SQL; 4.) Feature Engineering and Selection; 5.) Ads predictive model design; 6.) Ads predictive model offline training and model evaluation; 7.) Ads predictive model online/serving experiment and analysis; 8.) Ads modeling serving status monitoring and incident mitigation (Oncall); 9.) Distributed Systems; 10.) Prompt Engineering and RAG. Any suitable combination of education, training and/or experience is acceptable. Full time telecommuting is an option. Benefits: - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k with Employer Match - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave Submit a resume with references using the apply button on this posting or by email at: <a class="_ymio1r31 _ypr0glyw _zcxs1o36 _mizu194a _1ah3dkaa _ra3xnqa1 _128mdkaa _1cvmnqa1 _4davt94y _4bfu18uv _1hms8stv _ajmmnqa1 _vchhusvi _kqswh2mm _ect4ttxp _syaz13af _1a3b18uv _4fpr8stv _5