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Growth Marketing - Consumer App Channels
ABOUT ELEVENLABS ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. HOW WE WORK - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. - Excellence everywhere: Everything we do should match the quality of our AI models. - Global team: We prioritize your talent, not your location. WHAT WE OFFER - Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. - Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. - Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend. - Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. - Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy. - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. ABOUT THE ROLE ElevenReader is our fastest growing app that brings content to life for consumers. As we scale globally, we need a Growth Marketer who can turn creative ideas and strategic partnerships into one of our most powerful acquisition channels. You’ll own the strategy and execution of growth campaigns that bring millions of new users to ElevenReader through partnerships, integrated marketing, and innovative activations. Think: loyalty programs, co-marketing campaigns, OOH activations, offer-based collaborations, retail partnerships, and testing entirely new distribution channels. This is a highly cross-functional role that sits at the intersection of growth marketing, creative, partnerships, and performance marketing. You’ll develop creative campaigns, launch new acquisition channels, build scalable partnership playbooks, and rigorously measure what works. You’ll work closely with Performance Marketing to ensure every activation drives measurable full-funnel user growth while strengthening the ElevenReader brand. WHAT YOU WILL DO - Building and scaling strategic consumer partnerships that drive acquisitions for ElevenReader - Developing integrated marketing campaigns spanning partnerships, paid media, email, social, OOH, PR, and product surfaces - Expanding existing telecom & loyalty partnerships while launching new opportunities with partnersIdentifyin
ML Research Engineer - Narrative & AI Systems
As a ML Research Engineer on Embark's Machine Learning team, you will help shape the future of storytelling tools and systems for video games. We believe modern AI can unlock entirely new creative workflows for narrative design, quest building, lore creation, and player-facing reactivity. Our goal is to investigate how we can design new tools and systems that enable creators to be more ambitious, collaborate more effectively, and explore ideas with less friction rather than simply automating existing workflows. In this role, you will research, prototype, and build AI-driven narrative systems - exploring what's possible before optimizing for production. You'll work closely with writers, and designers to explore different levels of AI agency to intentionally design where AI agency makes sense and where it doesn't. This is a role for someone who is genuinely passionate about narrative and storytelling, has a research mindset, and is curious about what new AI techniques can enable in games. Example of responsibilities - Build gameplay systems and tools that enable new narrative workflows and faster iteration for creators - Collaborate with designers and narrative teams to understand creative needs and turn them into intuitive tooling - Research and prototype AI-driven narrative systems - quest generation, reactive dialogue, authoring tools, and beyond - Design and run lightweight experiments to evaluate creative AI applications - Work with writers and designers to explore and prototype AI-native gameplay mechanics that preserve authorial intent while enabling emergence and reactivity - Prototype experimental features quickly, then help mature the best ideas into robust solutions - Help design and evaluate different degrees of AI autonomy, balancing creative ambition, reliability, and control - Help define what 'good' looks like when AI is involved in storytelling We would love if you have - A research or engineering background with hands-on experience in ML or LLM applications - A genuine passion for narrative: games, film, interactive fiction, or otherwise - Curiosity and comfort working in ambiguous, exploratory problem spaces - A creator mindset: you enjoy building things that make other people more effective - Comfort collaborating with writers and designers and translating creative goals into technical solutions - Professional English communication skills Additionally, it's a bonus if you have - Experience working in Unreal Engine or with C++ - Experience with narrative systems, quest pipelines, or other creator-driven game features - A background in ML, NLP, generative models, or evaluation methodologies - Python experience, or interest in working across engine + services/tooling At Embark we offer competitive salaries, a generous profit-sharing program, and much more, but most of all we invite you to take part of a journey into the unknown, to build creative, surprising and beautiful experiences together. We welcome people from all backgrounds and are looking forward to reading more about you (in English)!
Sales Engineer (Bay Area)
ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Sales Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE You'll work on some of the hardest problems in applied AI alongside customers. This is not demos or research, but helping teams build systems they rely on in production. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, espec
Forward Deployed Engineer - ML
ABOUT US: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable https://modal.com/blog/lovable-case-study, Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C https://modal.com/blog/modal-series-c at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: - Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads on Modal - Contribute to open-source projects — members of the team are active contributors to SGLang — and publish technical content that demonstrates Modal's capabilities across the AI stack - Collaborate with Modal's product and sales teams, contributing to the platform as both an engineer and a product stakeholder - Build trusted relationships with technical leaders (CTOs, VPs of Engineering, ML leads) at companies doing frontier AI work - Conduct technical demos, experiments, and proof-of-concepts that make Modal's performance advantages tangible REQUIREMENTS: - 2+ years of professional ML engineering experience, ideally with hands-on work in inference optimization, model training, GPU programming, or ML infrastructure - Familiarity with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains. You don't need all of these, but you should be able to go deep on at least one. - Strong communicator who can go deep on technical architecture with an engineering team and clearly articulate tradeoffs to technical leadership - Genuine interest in working directly with customers — you find it energizing to understand someone else's problem and help them solve it - Bonus: side projects, open-source contributions, or published work you're proud of in ML or systems performance - Willing to work in-person in New York City, San Francisco, or Stockholm
Channel Account Manager
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Channel Account Manager for Japan, you will be responsible for building, managing, and scaling strategic partnerships with both System Integrators (SIs) and resellers to accelerate the adoption of our solutions in the Japanese enterprise market. You will work at the intersection of cutting-edge technology and Japan's unique business ecosystem, helping partners integrate our products into their solution portfolios and joint go-to-market strategies. As a Channel Account Manager, you will focus on growing reseller business in Japan and achieving quarterly revenue targets through new customers and upsells. The position involves direct collaboration with partners and internal teams to overcome obstacles and implement growth strategies. Responsibilities include designing partner recruitment, enablement, and go-to-market plans, using a test-and-learn approach in ambiguous situations. Strong business creation skills are needed to identify joint value propositions and explore co-selling models. While revenue contribution is the key metric, building scalable partner engagement and executing joint initiatives are crucial for consistent growth. This role is critical to establishing and expanding our presence in Japan through the partner ecosystem, enabling us to serve Japanese enterprises at scale. You will be instrumental in building our channel strategy from the ground up in one of the world's most sophisticated technology markets. Responsibilities: Strategic Partner Management - Develop and execute comprehensive business plans with System Integrators (NTT Data, Fujitsu, NEC, Hitachi, etc.) and key resellers to drive mutual growth and revenue targets - Build and maintain executive-level relationships within Japanese partner organizations, navigating complex organizational structures and decision-making processes - Own the full partner lifecycle from initial engagement through long-term strategic alignment, including regular business reviews and QBRs - Plan and deliver partner-facing activities, such as training sessions, email campaigns, webinars, and joint events - Negotiate and structure partnership agreements including technical integration terms, resale agreements, and revenue-sharing models Business Development & Revenue Generation - Build and maintain relationships with reseller and distributor partners to drive new customer acquisition and upsell revenue - Collaborate with SI partners and resellers to identify, qualify, and close enterprise opportunities in key verticals (manufacturing, financial services, retail, telecommunications, life sciences) - Drive joint sales activities including customer workshops, seminars, proof-of-concepts, and strategic account planning - Track pipeline development, forecast revenue, and report on partnership performance metrics with detailed accuracy - Manage channel conflic
Customer Success Manager, Beneficial Deployments -...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Join Anthropic as a Customer Success Manager supporting our Beneficial Deployments team’s initiatives in Global Development. In this role, you’ll apply enterprise-grade customer success practices to partnerships with mission-driven organizations. Anthropic’s Beneficial Deployments team is focused on building AI for good through partnerships with high-impact organizations. As their dedicated Customer Success Manager, you’ll be the strategic partner and trusted advisor to these organizations - helping them harness Claude’s full potential of all our Claude capabilities - API, Claude for Enterprise, and Claude Code to amplify their social impact. You’ll develop genuine partnerships with organizations, gaining a deep understanding of their mission, strategic objectives, programmatic goals, and technical capacity. Drawing on your global development expertise, business acumen, and technical knowledge, you’ll serve as a strategic advisor throughout their journey—helping them identify the right Claude capabilities for their specific objectives while providing best practices tailored to the unique needs of these institutions. Your role focuses on helping global development organizations scale their AI adoption effectively, implement change management strategies suited to mission-driven cultures, optimize use cases for maximum social impact, and demonstrate value that supports continued investment and expansion. The insights you gather from these partnerships will directly inform our research priorities, product development, and strategies for beneficial AI deployment—making you a key voice in shaping how we build and deliver AI systems that amplify social good. Key responsibilities: • Build trusting, strategic relationships with nonprofit leaders, program officers, and mission-driven stakeholders to understand their organizational goals, programmatic needs, and social impact objectives, identifying opportunities for optimization and expanded AI deployment in service of supporting their organizational transformation. • Become an expert in Anthropic’s products across API, Claude for Enterprise, and Claude Code, understanding the technical nuances and best practices for each to guide customers to the right solutions • Monitor usage patterns and proactively drive adoption—identifying optimization opportunities, addressing underutilization across consumption-based (API) and seat-based products, and discovering new applications for Claude across departments and workflows • Develop and execute change management strategies appropriate for mission-driven organizational cultures, driving adoption through Train the Trainer programs, Center of Excellence development, and organizational enablement that respects partner capacity constraints and decision-making processes • Create and maintain customer enablement resources—identifying opportunities to develop scalable assets that drive efficiency across the partner portfolio • Serve as the customer’s thought partner, enhancing their knowledge of Claude products by socializing Anthropic’s prod
Channel Account Manager, SI & Reseller
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Channel Account Manager for Japan, you will be responsible for building, managing, and scaling strategic partnerships with both System Integrators (SIs) and resellers to accelerate the adoption of our solutions in the Japanese enterprise market. You will work at the intersection of cutting-edge technology and Japan's unique business ecosystem, helping partners integrate our products into their solution portfolios and joint go-to-market strategies. As a Channel Account Manager, you will focus on growing reseller business in Japan and achieving quarterly revenue targets through new customers and upsells. The position involves direct collaboration with partners and internal teams to overcome obstacles and implement growth strategies. Responsibilities include designing partner recruitment, enablement, and go-to-market plans, using a test-and-learn approach in ambiguous situations. Strong business creation skills are needed to identify joint value propositions and explore co-selling models. While revenue contribution is the key metric, building scalable partner engagement and executing joint initiatives are crucial for consistent growth. This role is critical to establishing and expanding our presence in Japan through the partner ecosystem, enabling us to serve Japanese enterprises at scale. You will be instrumental in building our channel strategy from the ground up in one of the world's most sophisticated technology markets. Responsibilities: Strategic Partner Management - Develop and execute comprehensive business plans with System Integrators (NTT Data, Fujitsu, NEC, Hitachi, etc.) and key resellers to drive mutual growth and revenue targets - Build and maintain executive-level relationships within Japanese partner organizations, navigating complex organizational structures and decision-making processes - Own the full partner lifecycle from initial engagement through long-term strategic alignment, including regular business reviews and QBRs - Plan and deliver partner-facing activities, such as training sessions, email campaigns, webinars, and joint events - Negotiate and structure partnership agreements including technical integration terms, resale agreements, and revenue-sharing models Business Development & Revenue Generation - Build and maintain relationships with reseller and distributor partners to drive new customer acquisition and upsell revenue - Collaborate with SI partners and resellers to identify, qualify, and close enterprise opportunities in key verticals (manufacturing, financial services, retail, telecommunications, life sciences) - Drive joint sales activities including customer workshops, seminars, proof-of-concepts, and strategic account planning - Track pipeline development, forecast revenue, and report on partnership performance metrics with detailed accuracy -
Manager, Account Executive - GSIs
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Sales Manager at Anthropic, you’ll lead a team of Strategic Account Executives driving the adoption of safe, frontier AI by winning and growing the world’s largest global systems integrators and consultancies — as both strategic customers and go-to-market partners. You’ll leverage your leadership and consultative sales expertise to propel revenue growth while developing a high-performing team of AEs. Working closely with Applied AI Engineering, Partnerships, and Product teams, you’ll help partners embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM and Marketing teams, you’ll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape. The ideal candidate will have a passion for developing people, identifying market opportunities, and executing strategies to capture them. By leading the deployment of Anthropic’s emerging products, you will help systems integrators and their clients obtain new capabilities while also advancing the ethical development of AI. Responsibilities: - Recruit, coach, and retain Strategic Account Executives with deep partner/alliance and platform-selling expertise; develop leadership talent and create career paths that keep top performers growing - Codify the use cases, proof points, reference stories, and sales motions that make wins repeatable across each GSI partner and across both the sell-to and co-sell motions, partnering with Marketing, Enablement, Partnerships, and the partners themselves to scale them - Engage personally with C-level executives at the GSIs — and, on co-sell pursuits, at their enterprise clients — building business cases and value narratives and navigating complex procurement, security, and legal processes through to production deployment and expansion - Own the organization's revenue targets and operating rhythm, instilling pipeline-generation discipline and running forecasting, deal inspection, and account planning cadences that make performance predictable and coachable across both the internal-adoption and co-sell pipeline - Partner closely with Applied AI, Solutions Architecture, and Product to design solutions, prove value quickly, and translate partner and client needs into product and roadmap input - Orchestrate cross-functional and partner motions with Customer Success, Marketing, Partnerships (PAMs), Legal, and cloud partners to deliver a seamless experience, and represent Anthropic with partners and at industry events as a visible, trusted leader You may be a good fit if you have: - Experience leading strategic sales teams that sell technical, complex products such as API-first platforms, cloud infrastructure, or data and machine learning platforms - A track record of winning and growing strategic customers and/or partners, including building C-suite relationships, ideally with global systems integrators, consultancies, or other large partner/alliance ecosystems - Experience designing go-to-market coverage for a strategic sales team, including account and partner prioritization - Operational rig
Engineering Manager, Safeguards Review Tooling
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Safeguards team is responsible for ensuring our models and products are developed and deployed safely. We're looking for an Engineering Manager to lead our Review Tooling team, which builds the systems that humans — and increasingly Claude — use to investigate potential harms and take enforcement actions across Anthropic's first-party products and third-party cloud platforms. This is a foundational role: you'll own the tools our safety investigators rely on to understand what's happening on our platforms and act on it, as well as the platform underneath those tools. That platform includes analytics capabilities, privacy-preserving primitives that keep review workflows compatible with our data retention commitments, and a sandbox environment where new review interfaces and workflows can be built and iterated quickly. As model capabilities and usage grow, you'll also drive how we scale review through automation — building systems where Claude meaningfully extends what human reviewers can do, while keeping people in the loop where their judgment matters most. You'll partner closely with policy, operations, data science, and legal teams to ensure our enforcement systems are effective, accurate, and trustworthy. Key responsibilities - Lead, grow, and develop a team of engineers building investigation, review, and enforcement tooling for both first-party and third-party platform surfaces - Define the vision and roadmap for our review tooling platform, including analytics, privacy-compatible data access primitives, and a sandbox for rapidly developing new review interfaces - Drive the team's strategy for scaling review through automation, including enabling reviewers to use Claude effectively and building toward Claude-assisted and Claude-driven review workflows - Partner with policy, operations, legal, privacy, and data science stakeholders to translate enforcement and investigation needs into reliable, well-designed systems - Ensure review tooling evolves alongside new privacy primitives and data retention commitments, so reviewers can do their work without compromising user trust - Create clarity for the team and stakeholders in an ambiguous and evolving environment - Take an inclusive, equitable approach to hiring and coaching top technical talent, and maintain a high-performing team - Contribute to engineering-wide initiatives as a member of Anthropic's engineering management community Minimum qualifications - Experience managing software engineering teams, including hiring, coaching, and developing engineers - A technical background in full-stack or platform engineering, with the ability to engage deeply in architecture and design discussions - Experience shipping internal tools or platforms with demanding operational users, and a track record of improving their workflows measurably - Experience working cross-functionally with non-engineering partners such as operations, policy, or legal teams - Excellent communication skills, including the ability to explain technical tradeoffs to non-technical stakeholders - Care about the societal impacts of AI and want your work
Strategic Account Executive, Cybersecurity
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Strategic Account Executive focused on cybersecurity, you'll own some of Anthropic's most strategic cybersecurity relationships—companies building the next generation of AI-powered security products. These aren't typical enterprise accounts; they're partners shaping how AI transforms the entire security industry. You'll drive multi-million dollar commitments by expanding Claude's footprint across customer product portfolios (AI-powered SOC, threat detection, security copilots) and internal operations (Claude Code for engineering teams). You'll work at the intersection of executive relationships and technical depth—one week you're in a CTO strategy session, the next you're helping an engineering team scope an agentic deployment. This role requires someone who can think like a partner, not just a seller. You'll collaborate closely with our Applied AI team on custom deployments, work with Product on cybersecurity-specific capabilities, and help shape Anthropic's go-to-market in one of our highest-potential verticals. Responsibilities: - Win business and drive revenue within a book of strategic cybersecurity accounts.Own the full sales cycle from prospecting to close - Drive expansion across multiple buying centers within strategic accounts—product teams building customer-facing AI features, platform teams deploying Claude Code to engineering orgs, and security research teams exploring frontier capabilities - Navigate complex organizational structures across security, product, engineering, and executive teams. Build multi-threaded relationships with CISOs, security architects, product and engineering leaders, and C-suite executives - Partner with Solutions Architect and Product teams on technical scoping, custom agent development, and enterprise deployments - Design and execute innovative sales strategies tailored to the cybersecurity market. Analyze account landscape, competitive dynamics, and emerging security trends to inform targeted sales activities - Identify and develop use cases across security operations (SecOps automation, threat hunting, alert triage), security product development (AI-powered detection, intelligent response), and internal security functions - Navigate unique considerations of AI in security contexts, including model guardrails, responsible deployment, and emerging use cases like AI red-teaming - Own sophisticated deal cycles involving security evaluations, red team assessments, and complex procurement processes. Navigate security and compliance requirements with patience and expertise - Build and maintain accurate pipeline forecasting for complex, multi-workstream accounts. Develop deep understanding of how large security vendors budget for AI infrastructure across product and internal use cases - Serve as the voice of the cybersecurity customer internally. Inform product roadmaps by gathering feedback on security-specific requirements, compliance needs, and competitive gaps
Customer Success Manager, Industries
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Join Anthropic's Customer Success team in a high-impact role driving AI adoption across our Industry segment. As an Enterprise Customer Success Manager for Industries, you'll be the strategic partner and a trusted advisor to our most complex customers with a portfolio spanning Financial Services, Systems Integrators, Semiconductor, Manufacturing and Retail organizations—helping them harness the full potential of all our Claude capabilities - API, Claude for Enterprise, and Claude Code. You'll work with organizations across diverse industries that are transforming their businesses with AI technology. Developing genuine partnerships with customers, gaining a deep understanding of their business objectives, strategic direction, AI vision, and technical needs. You'll draw on both your business acumen and technical expertise to serve as a strategic advisor throughout their journey with us. In partnership with the broader account team you will help customers identify the right Claude capabilities for their specific business objectives, working closely with them to provide best practices and guidance while supporting them as their usage (consumption & seat based) grows and evolves. Your role focuses on helping customers scale their usage effectively, drive model and use case optimizations, implement change management strategies, and maximize the value of their investment through expanded use cases across their organization. The insights you gather from your customers will directly inform our research priorities, product development, and go-to-market strategies — making you a key voice in shaping how we build and deliver ongoing value as a business. Responsibilities: - Build trusting, strategic relationships with key customer decision makers to understand their business and objectives, identifying opportunities for optimization and expansion - Become an expert in Anthropic's products across API, Claude Code and Claude for Enterprise, understanding the technical nuances and best practices for each to guide customers to the right solutions - Leverage your deep knowledge of the customer and their industry vertical to proactively drive usage planning, understanding current and future consumption/adoption and how it creates realized value for the customer - Monitor usage patterns and identify optimization opportunities, proactively addressing underutilization across both consumption-based (API) and seat-based (Claude for Enterprise / Claude Code) products to drive full value from contracted commitments - Serve as the customer's thought partner, enhancing their knowledge of Claude products by socializing Anthropic's product roadmap, driving awareness on new products and engaging Product PMs - Document and quantify customer value realized through business outcomes, ROI, and impact metrics to build compelling internal business cases for continued and expanded investment - Identify potential use cases and lines of business not currently onboarded, partnering with customers and Sales to discover new applications for Claude across different departments, teams, and workflows - Develop and execute change management strategies to drive end-user adoption and maximize
Mid-Market Account Executive, Industries
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Mid-Market Account Executive on Anthropic's Industries team, you'll drive the adoption of safe, frontier AI by securing strategic deals with mid-market companies in key verticals, unlocking new value streams throughout their business. You'll leverage your consultative sales expertise and technical acumen to propel revenue growth while becoming a trusted partner to customers, helping them embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM, Product, Engineering, and cross-functional teams, you'll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape. You will be contributing to the GTM strategy for our Industries team, focusing on sector-specific solutions and strategies within key verticals. In addition, the Mid-Market team is pioneering a new scaled sales playbook, where human AEs direct AI Agents to automate key elements of the buyer’s journey, while maintaining human engagement with prospects in the elements of a sales process that can’t be automated. You should be passionate about building a fundamentally new sales motion, by experimenting with new programs and workflows, and ultimately evangelizing the potential of Transformative AI to mid-market companies across verticals. Responsibilities: - Contribute to the Mid-Market GTM strategy, identifying new use cases within your assigned verticals, winning new business, and sharing feedback with cross-functional teams - Drive strategic expansion within key accounts in established verticals and new logo acquisition within emerging verticals - Own a revenue target and all aspects of the sales cycle from prospecting to close, including finding key workflows to automate and agentify - Become a trusted advisor to customers, understanding their unique needs and crafting tailored AI solutions. Co-innovate with customers and sell on the product roadmap while appropriately setting expectations - Collaborate extensively with cross-functional partners including Product, Customer Success, Legal, Marketing, and Applied AI to help bring new solutions to market and provide feedback to shape roadmaps - Develop sales collateral, proposals, and presentations to effectively position Anthropic's AI products. Continuously refine sales tactics and share best practices You may be a good fit if you have: - 3+ years of enterprise B2B sales experience in technology, preferably in SaaS, API solutions, or emerging technologies - Experience automating workflows or building automations to handle the repeatable components of a sales process - Proven experience exceeding revenue targets in fast-paced organizations by effectively managing an evolving pipeline and sales process - Excellent communication skills and the ability to present confidently and build connections across all customer levels, from ICs to C-level executives - A knack for bringing order to chaos and an enthusiastic “roll up your sleeves'' mentality. You are a true team player - A strategic, analytical approach to assessing markets combined with creative, tactical execution to cap
Customer Success Programs Manager
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role At Anthropic, we believe the next generation of Customer Success looks fundamentally different; most customer outcomes will be delivered through programs, not 1:1 relationships, and increasingly without a human in the loop. As a Success Programs Manager , you'll own a portfolio of those programs and flex across whatever the function needs to drive adoption and value at scale. As a CS Programs Lead you’ll think "How could we do this with Claude?" as a reflex — your default is to build an agent or an automated journey before you build a manual workflow. But you're also fluent in the craft of running engagements: you've personally designed and delivered 1:many webinars, stood up onboarding cohorts, and built communities that compound. You move comfortably between shipping an AI-native lifecycle flow on Monday and facilitating a live customer cohort on Tuesday. You'll work across the full Claude product surface, designing and shipping the programs that take customers from activation to value realization, expansion, and renewal. Instead of managing a book of accounts, you'll manage a portfolio of programs, each one a compounding asset that serves more customers, more effectively, every week it ships. You hold a high bar for measurable impact, you instrument what you build, and you retire what doesn't earn its keep. If the idea of a CS team that builds and ships as much as it joins calls excites you, and you want the range to do both, this role is for you. Key responsibilities: - Build and run a portfolio of programmatic CS plays (activation, scale and expand) across the long tail and unmanaged segments, spanning Claude Enterprise; Cowork, and Claude Code. - Design and ship Claude-powered engagement plays that replace or augment traditional CSM touchpoints: use-case discovery chats, digital QBRs, health reviews, feature nudges, consumption-drop saves, and expansion prompts. Define entry criteria, agent behavior, exit criteria, and success metrics for each. - Design and deliver high-leverage live engagements. 1:many webinar series, onboarding cohorts, customer communities, and academies, and look for every opportunity to make them AI-native, repeatable, and self-serve over time. - Flex across the needs of the function. Some weeks the priority is an agent; some weeks it's a cohort or a community launch. You bring comprehensive knowledge of what effective CS programs look like and apply the right model to the problem in front of you. - Instrument every program with consumption, product telemetry, and qualitative signals. Know which touchpoints — digital or live — deliver the most value and where the handoff between digital and human should sit, and invest accordingly. - Treat every cohort as an experiment. Continuously iterate on agent prompts, workflow logic, content, facilitation, and channel mix. Hold a high bar for measurable impact; kill plays that don't move the numbers. -
Site Security Manager, Industrial Security
Scale is at the forefront of powering artificial intelligence. We believe that trust in AI is earned with high-quality data for training, fine-tuning, and evaluating AI systems. Our products are transforming how organizations build and deploy AI. Our customers are the world’s most innovative model developers and enterprise and public sector entities looking to apply AI in their organizations and institutions. We're looking for a Site Security Manager who will play a vital role in supporting industrial security, physical security and program support. The ideal candidate brings strategic and operational experience, a security-first mindset, and a willingness to engage directly with customers, employees and stakeholders. If you're excited by ensuring the integrity and protection of national security, we invite you to apply. Site Security Manager will report to the Industrial Security team with close collaboration with Physical Security, Workplace, and cross-functional teams to support the Public Sector security strategy for Scale. - Oversee the construction, modification, and expansion of SCIFs in accordance with ICD 705 and TEMPEST requirements. - Work closely with engineering, architecture, and general contracting teams to ensure all physical security requirements are implemented effectively and efficiently - Ensure the SCIF meets or exceeds all requirements under ICD 705, ICD 705-1 (Physical and Technical Security Standards), and ICD 705-2 (Technical Specifications) - Experience managing the SCIF accreditation lifecycle: initial accreditation, interim accreditation, re-accreditation, and de-accreditation - Implement and enforce Standard Operating Procedures (SOPs) for SCIF operations - Familiarity with the Cognizant Security Authority (CSA) and Accrediting Official (AO) relationship, including how to prepare documentation packages, coordinate inspections, and manage waivers. - Support all aspects of personnel security management in working directly with government partners to ensure compliance - Responsible for mandatory USG reporting as it relates to our personnel, facility, and insider threat programs - Maintain COMSEC material accountability - Proficiency in implementing and maintaining access controls, visitor management systems, and security documentation in accordance with national security protocols - Provide ongoing training and guidance to ensure adherence to classified material handling and facility protocols - Experience maintaining the Fixed Facility Checklist and SCIF repository reporting requirements. - Investigate and report security incidents, violations, and anomalies to the FSO/ITPSO in accordance with Scale AI's Insider Threat Program Plan and NISPOM requirements Ideally you'd have: - Active U.S. Top Secret clearance, and willingness to obtain a TS/SCI - Minimum 3+ years of experience managing or operating a SCIF or similar classified facility - Familiarity with USG information systems, such as DISS, NBIS, NISS, SWFT, e-App - ICD-705 Certification - Must be able to support work 3 days a week from the office - Working knowledge of ICD 705, NISPOM (32 CFR Part 117), and related Intelligence Community directives - Familiarity with Intrusion Detection Systems, access control systems, and TEMPEST requirements - Experience with government security databases (e.g., DISS, NISS, Scattered Castles) Nice to haves: </
Workplace Operations Specialist
We are looking for a Workplace Operations Specialist to lead day-to-day workplace operations for our San Francisco office and support our Palo Alto office through regular onsite presence. This role will help create a welcoming, productive, safe, and engaging office experience for employees, candidates, customers, and visitors. You will partner closely with People, Finance, IT, Security, Legal, Events, Recruiting, and local office stakeholders to ensure our workplace programs and services support employee connection, operational excellence, and the company’s broader talent strategy. Our Workplace team is responsible for creating office environments that feel human, energizing, inclusive, and thoughtfully designed. We set high standards for how people experience work every day and help ensure employees feel supported, connected, and motivated throughout their careers. ABOUT US Perplexity is a San Francisco based AI “answer engine” founded in 2022 and was created to rethink how people search for and consume information. Our mission is to democratize access to knowledge by providing fast, accurate, and transparently cited answers in natural language rather than long lists of links. We are guided by a vision of making information retrieval more conversational, trustworthy, and accessible to everyone. Perplexity has expanded from a web product into browser extensions, mobile apps, and a Pro offering while positioning itself as an AI‑native alternative to traditional search. WHAT YOU’LL DO WORKPLACE STRATEGY AND EMPLOYEE EXPERIENCE - Support the development and execution of workplace programs that align with company values, employee needs, and business priorities. - Partner with Events and People teams to create in-office experiences that encourage connection, collaboration, and productivity. - Help design a consistent and engaging office experience for local employees, visiting employees, candidates, customers, and guests. - Identify opportunities to improve workplace services, office usage, employee experience, and operational efficiency. - Promote a culture of inclusion, hospitality, collaboration, and productivity across assigned office locations. OPERATIONS AND FACILITIES MANAGEMENT - Manage daily workplace operations for the San Francisco office and support the Palo Alto office through weekly visits and additional travel as needed. - Oversee core workplace services, including food and beverage, snacks, cleaning, maintenance, front desk, guest services, office supplies, and site readiness. - Partner with local office leads and vendors to maintain consistent quality, service, and maintenance standards across assigned offices. - Coordinate proactive maintenance, space planning, office repairs, and workplace improvement projects. - Help implement standardized workplace programs, policies, and practices in collaboration with internal partners and local office stakeholders. BUDGET, VENDORS, AND PROCUREMENT - Manage workplace budgets, invoice review, purchase approvals, and expense tracking in partnership with Finance. - Prepare and maintain proposals for workplace initiatives, including scope, budget, timeline, business rationale, and expected impact. - Evaluate vendor performance, negotiate service improvements, and identify cost-saving opportunities related to facilities, services, and workplace programs. - Ensure workplace expenses are accurately allocated and aligned with organizational goals. HEALTH, SAFETY, AND EMERGENCY PREPAREDNESS - Partner with internal teams to support workplace health, safety, and emergency preparedness programs. - Coordinate emergency response planning, drills, employee communications, and office-specific readiness materials. - Help ensure employees have access to relevant safety information, emergency procedures, and workplace resources. - Support compliance with applicable company policies and local workplace requirements. CROSS-FUNCTIONAL COLLABORATION - Build and maintain strong relationships with in
Machine Learning Infrastructure Engineer, Safeguar...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Safeguards team builds the systems that detect and mitigate misuse of our AI models, from individual policy violations to sophisticated, coordinated attacks. A growing part of that work depends on lightweight detection methods trained on model internals, which let us identify harmful behavior cheaply and at scale. This work feeds directly into Anthropic's Responsible Scaling Policy commitments. We're looking for an engineer to own the infrastructure behind that research. This is the tooling our researchers rely on to run experiments, train detection methods, and select detections for launch. It sits between research and production: researchers depend on it for fast iteration, and our detection systems depend on it for reliable, correct results as our models continue to change. Running machine learning workloads at our scale often requires solving novel systems problems. You'll identify those problems and build the abstractions, pipelines, and tooling that keep the research loop fast as requirements shift underneath you. Strong candidates will have a track record of solving large-scale systems and data problems and will be excited to grow deep machine learning expertise alongside it. Key responsibilities - Build and scale the infrastructure and data pipelines behind Safeguards machine learning research - Own the training, evaluation, and scoring workflows researchers use, with a focus on cutting the time between an idea and a result - Design tooling and interfaces, including libraries and command line tools, that researchers can use directly without needing to understand the systems underneath - Build correctness and sanity checking into the stack, so results stay trustworthy as models and workloads evolve - Take the highest-value research workflows from experiments to reliable, production-grade jobs - Improve the throughput, cost, and reliability of large-scale inference and scoring workloads - Partner closely with researchers and engineers across Safeguards to understand their workflows, anticipate how their needs will change, and design for that ahead of time Minimum qualifications - Strong software engineering fundamentals and hands-on coding ability, with proficiency in Python - Experience building and operating data-intensive or distributed systems in production - Experience building tooling or infrastructure that other engineers or researchers use as a dependency - Comfort working across the research-to-deployment pipeline, from exploratory experiments to production systems - Ability to debug performance and correctness problems across an unfamiliar stack - Strong written and verbal communication skills, and a collaborative approach to technical decisions Preferred qualifications - Experience with high-performance, large-scale machine learning systems - Familiarity with language modeling and transformers, including working with model internals - Experience
Engineering Manager, GRC Platform
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking an Engineering Manager, GRC to join our GRC organization and build the technical foundation for how we scale our risk and compliance programs. In this role, you will lead the team that designs and implements automated workflows, data pipelines, and integrations that transform manual compliance processes into scalable engineering systems. This is a greenfield opportunity to establish the team, architecture, and integrations that will define how we approach governance, risk, and compliance at Anthropic. The core challenge is a data problem: compliance information lives across dozens of systems—cloud infrastructure, identity providers, HR platforms, ticketing tools, code repositories—and your job is to design systems that bring it together, normalize it, and make it actionable. Success in this role comes from understanding how systems connect and how data flows between them. At Anthropic, you'll also have a unique advantage: the ability to design AI-powered workflows where Claude acts as an extension of your team, handling tasks that would traditionally require additional headcount or manual effort. You'll need ingenuity to identify where agentic AI can accelerate evidence collection, interpret unstructured data, triage compliance gaps, and augment human judgment in risk assessments. Working closely with Security, IT, and Engineering teams, you'll translate compliance and regulatory requirements into solutions that support audit programs including SOC 2, ISO, HIPAA, and FedRAMP, building systems that combine traditional automation with AI capabilities to achieve scale that wouldn't otherwise be possible. Key responsibilities - Lead the team that establishes foundational GRC processes and architecture. Design and build automated workflows for risk management and compliance, creating scalable systems that enable continuous monitoring as Anthropic grows. - Build data pipelines that aggregate risk, control, and asset information from across our technology stack. This means solving hard data integration problems: mapping disparate schemas, handling inconsistent data quality, and creating unified views of compliance posture through dashboards and reporting tools. - Inform GRC platform strategy and implementation: in partnership with other programs, plan for and build tooling that meets our compliance requirements. - Translate written policies and compliance requirements into policy-as-code—working with Engineering and Security teams to express requirements as enforceable rules, automated checks, and continuous validation rather than static documents. - Establish feedback loops between policy and implementation: surface where technical controls diverge from written requirements, identify where policies need to evolve based on infrastructure realities, and ensure that compliance requirements are expressed in terms engineers can act on. - Design and deploy agentic AI workflows that extend team capacity, using Claude to serve as a virtual GRC analyst to automate evidence analysis, monitor control effectiveness, draft audit responses, interpret policy documents, and handle other tasks that require reasoning over unstructured information. <
Manager, Applied AI Engineering (Enterprise)
About the Team The Technical Success team helps OpenAI’s customers realize meaningful and sustained value from our technology. We partner with customers throughout their journey—from initial exploration and solution design to production implementation and organization-wide adoption. Applied AI Engineers serve as trusted technical partners to customer executives, engineering teams, product leaders, security organizations, and transformation teams. They combine deep technical judgment with strong customer instincts, translating frontier AI capabilities into secure, reliable systems and durable business outcomes. About the Role We are seeking a Manager to build, lead, and develop a high-performing team of Applied AI Engineers supporting our enterprise customers. You will be accountable for the technical success of a broad and strategically important customer portfolio. You will help your team identify high-value opportunities, design and deploy production-grade AI systems, navigate complex technical and organizational constraints, and expand successful implementations across workflows, teams, and business units. This role requires technical depth, people leadership, customer judgment, and operational rigor. You should be comfortable coaching engineers through architecture and evaluation decisions, engaging directly in high-stakes customer situations, and collaborating with Sales, Solutions Engineering, Product, Research, Engineering, Security, and Legal. You will also help define how we serve enterprise customers at scale by developing effective coverage models, reusable implementation patterns, technical enablement, escalation mechanisms, and systems for turning field insights into high-quality product feedback. In This Role, You Will - Build, manage, and develop a high-performing team of Applied AI Engineers supporting large and complex enterprise customers. - Own the quality and impact of the team’s work across solution design, implementation, production readiness, adoption, and expansion. - Coach the team through decisions involving architecture, model selection, evaluations, reliability, latency, safety, security, governance, and cost. - Establish an operating model for prioritizing accounts and engagements according to customer needs, strategic value, technical complexity, and potential for repeatable impact. - Serve as a senior technical escalation point during critical launches, production incidents, complex integrations, and high-stakes customer decisions. - Partner with customer executives and technical leaders to connect implementation decisions to measurable business and operational outcomes. - Help customers progress from experimentation to production systems and sustained adoption across their organizations. - Partner closely with Sales and Solutions Engineering to create continuity throughout the customer lifecycle and maintain shared accountability for customer success. - Translate customer needs and recurring implementation challenges into actionable feedback for Product, Research, Engineering, Security, and other internal teams. - Identify scalable market patterns, distinguish them from bespoke requests, and advocate for investments that can benefit multiple customers. - Develop reusable architectures, evaluation methods, playbooks, tooling, and enablement that improve time to value across the enterprise portfolio. - Establish mechanisms for measuring production implementations, adoption, customer outcomes, delivery quality, team capacity, and the impact of reusable work. - Hire thoughtfully, raise the technical and leadership bar, and foster a culture of accountability, curiosity, collaboration, inclusion, and continuous learning. - Represent OpenAI with credibility and sound judgment in conversations with senior customer and internal stakeholders. You Might Thrive in This Role If You - Have significant experience managing customer-facing technical teams, such as Applied AI Engineers, Solutions Architects, Forward Deployed Engineers, Customer Engineers, or Technical Account Managers. - Have built or led teams responsible for implementing complex software, data, machine learning, or AI systems in enterprise environments. - Maintain sufficient technical depth to evaluate architectures, ask incisive questions, challenge assumptions, and coach engineers through difficult implementation decisions. - Have experience taking AI, machine learning, or other technically complex systems from prototype to production. - Understand production-system requirements, including reliability, observability, security, privacy, data governance, evaluation, and operational readiness. - Have led teams through ambiguity, competing priorities, escalations, and rapidly evolving products or markets. - Can translate effectively among technical details, customer needs, product strategy, and business outcomes. - Have worked with large organizations involving multiple business units, stakeholder groups, procurement processes, or governance requirements. - Demonstrate strong executive presence and can build trust with engineering leaders, business executives, security teams, and other senior stakeholders. - Have designed operating models, coverage strategies, prioritization frameworks, or repeatable delivery processes for a growing technical organization. - Are a strong cross-functional partner who can navigate disagreement directly while maintaining trust and shared accountability. - Use data and clear principles to allocate limited resources across a large portfolio of opportunities. - Care deeply about developing people and have a track record of coaching team members, raising performance, and building inclusive teams. - Are energized by helping organizations adopt frontier AI responsibly and turn emerging capabilities into durable value. Relevant Experience May Include - Leading teams in applied AI engineering, solutions architecture, forward-deployed engineering, professional services, technical consulting, or customer engineering. - Implementing generative AI, machine learning, developer platforms, cloud infrastructure, data platforms, or other complex enterprise technologies. - Working with customers in semiconductors, media, entertainment, or similarly complex and technology-intensive industries. - Supporting global customers, multi-business-unit implementations, regulated workflows, or large-scale organizational transformations. - Building technical enablement, reusable solution patterns, evaluation frameworks, or customer implementation methodologies. Direct experience in these industries is not required. We value leaders who can recognize common technical and organizational patterns while adapting their approach to different customer environments. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Social Media Manager
Perplexity is looking for a Social Media Manager to expand how Perplexity shows up online. You'll run the channels day to day, writing posts, setting strategy, scaling our accounts, and writing for leadership and the team, working closely with our Communications and marketing team, product managers, and engineers. This is a hands-on role. You'll write most of what goes out yourself. Excellent judgement and high taste are required. The role is mostly Instagram with some community initiatives like Reddit, and interacting with our developer audiences. RESPONSIBILITIES - Run social channels day to day. Maintain our brand and product accounts across all channels. This includes writing social copy, planning content, and managing engagement. - Set the social strategy. Decide and execute how we grow each account, what we post where, and how we measure it. - Scale our team accounts. Help employees post in our voice and grow our presence across platforms. - Build and moderate community. Engage on Reddit and in developer communities, and represent Perplexity where our users already are. - Adapt and ship fast. Partner with Comms and marketing, PM’s, founders, and engineers in a fast-paced launch environment. QUALIFICATIONS - 3+ years running social for a brand, ideally tech and AI. - You can write. Send us posts you wrote that performed and tell us why they worked. - Native fluency on Instagram and LinkedIn, with a track record of growing an account. - Demonstrated experience being entrusted with a brand voice - You know how to write for different audiences and platforms, and adjust the voice for each. - Comfortable in a fast launch cycle where the plan changes often NICE TO HAVE - You've run or moderated a developer or technical community. - You've written on behalf of leadership or other voices. - You follow AI closely and have opinions on how the best companies show up online.
Red Team Engineer, Safeguards
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Safeguards team is seeking a Red Team Engineer to help ensure the safety of our deployed AI systems and products. In this role, you'll take an adversarial approach to uncover vulnerabilities across our product ecosystem before they can be exploited by malicious actors. Your work will span from technical infrastructure vulnerabilities on our products to emergent risks from advanced AI capabilities. While you'll bring best practices from traditional security approaches, the focus is on broader safety implications and novel abuse unique to advanced AI systems and associated products. You'll investigate the full spectrum of potential abuse — from coordinated account manipulation and payment fraud to novel exploitation of product features — and simulate sophisticated threat actors who chain multiple attack vectors to achieve their objectives. Key responsibilities - Conduct comprehensive adversarial testing across Anthropic's product surfaces, developing creative attack scenarios that combine multiple exploitation techniques - Research and implement novel testing approaches for emerging capabilities, including agent systems, tool use, and new interaction paradigms - Design and execute "full kill chain" attacks that emulate real-world threat actors attempting to achieve specific malicious objectives - Build and maintain systematic testing methodologies that evaluate every aspect of our systems - Develop automated testing frameworks to enable continuous assessment at scale - Collaborate with Product, Engineering, and Policy teams to translate findings into concrete improvements - Help establish metrics for measuring detection effectiveness of novel abuse Minimum qualifications - Experience in penetration testing, red teaming, or application security - Experience in model jailbreaking and testing large-scale agentic workflows for non-obvious prompt injection vectors - Strong technical skills in web application security, including hands-on expertise with security testing tools (e.g., Burp Suite, Metasploit, custom scripting frameworks) - Experience building custom automation, including LLM-specific testing frameworks - A track record of discovering novel attack vectors and chaining vulnerabilities in creative ways - A public body of work such as CVEs, blog posts, or disclosed bug bounty reports - Strong written and verbal communication skills, with the ability to explain technical concepts to varied audiences Preferred qualifications - Experience with AI/ML security or adversarial machine learning - Understanding of AI safety considerations beyond traditional security, including modern guardrails against jailbreaks - Experience testing API security and rate-limiting systems - Background in testing business logic vulnerabilities and authorization bypass techniques - Background in anti-fraud, trust & safety, or abuse prevention syste
Software Engineer, Accelerators
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role On the Accelerators team, you will help OpenAI evaluate and bring up new compute platforms that can support large-scale AI training and inference. Your work will range from prototyping system software on new accelerators to enabling performance optimizations across our AI workloads. You’ll work across the stack, collaborating with both hardware and software aspects - working on kernels, sharding strategies, scaling across distributed systems, and performance modeling. You'll help adapt OpenAI's software stack to non-traditional hardware and drive efficiency improvements in core AI workloads. This is not a compiler-focused role, rather bridging ML algorithms with system performance - especially at scale. In this role, you will: - Prototype and enable OpenAI's AI software stack on new, exploratory accelerator platforms. - Optimize large-scale model performance (LLMs, recommender systems, distributed AI workloads) for diverse hardware environments. - Develop kernels, sharding mechanisms, and system scaling strategies tailored to emerging accelerators. - Collaborate on optimizations at the model code level (e.g. PyTorch) and below to enhance performance on non-traditional hardware. Perform system-level performance modeling, debug bottlenecks, and drive end-to-end optimization. - Work with hardware teams and vendors to evaluate alternatives to existing platforms and adapt the software stack to their architectures. - Contribute to runtime improvements, compute/communication overlapping, and scaling efforts for frontier AI workloads. You might thrive in this role if you have: - 3+ years of experience working on AI infrastructure, including kernels, systems, or hardware-software co-design - Hands-on experience with accelerator platforms for AI at data center scale (e.g., TPUs, custom silicon, exploratory architectures). - Strong understanding of kernels, sharding, runtime systems, or distributed scaling techniques. - Familiarity with optimizing LLMs, CNNs, or recommender models for hardware efficiency. - Experience with performance modeling, system debugging, and software stack adaptation for novel architectures. - Exposure to mobile accelerators is welcome, but experience enabling data center-scale AI hardware is preferred. - Ability to operate across multiple levels of the stack, rapidly prototype solutions, and navigate ambiguity in early hardware bring-up phases - Interest in shaping the future of AI compute through exploration of alternatives to mainstream accelerators. To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Commercial Counsel, Platform & Marketplace
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As Commercial Counsel for Platform & Marketplace at Anthropic, you'll support scaling up go-to-market motions and platforms like the Claude Marketplace, which lets enterprise customers discover, buy, and pay for third-party applications. You'll be the trusted legal partner to Business Development teams within Anthropic’s Partnerships & Alliances org, shaping how we collaborate with sellers and customers on existing and future platforms. You’ll not only focus on how we interact with our own resale channels but also on how we participate in third-party marketplaces. We'll count on you to own, negotiate, and continuously improve the core contracting vehicles for these go-to-market programs, as well as supporting terms that sit between sellers and buyers. Key responsibilities - Own end-to-end legal strategy and execution for certain partnership ecosystems and contracting programs - Serve as one of the legal partners to our Partnerships & Alliances business team, functioning as a strategic advisor embedded in partnership planning - Independently lead complex, multi-party negotiations involving technical integrations, revenue-sharing arrangements, joint go-to-market strategies, and strategic commitments that may implicate other Anthropic business relationships - Architect scalable partnership frameworks, templates, and programs that enable the broader organization to execute deals efficiently while maintaining appropriate risk controls - Provide strategic counsel on partnership structures that balances legal risk management with aggressive growth objectives - Coordinate cross-functionally with Compute, Strategic Pursuits, Finance, and GTM teams on deals where partnership terms interact with other commercial relationships and commitments Minimum qualifications - JD and active membership in at least one U.S. state bar (California preferred) - Demonstrated track record of independently leading complex, multi-stakeholder negotiations with major technology companies that resulted in successful partnership launches, including situations where Anthropic's interests must be balanced against partners and end customers simultaneously - Experience serving as the go-to legal partner for a partnerships or business development organization; the attorney that business leaders actively want in strategy sessions - Deep understanding of partnership economics: how deal registration works, why revenue attribution matters to partners, how to structure incentives that align interests, and what motivates a partner to prioritize one vendor over another - Superior judgment in risk assessment and strategic tradeoffs, with the confidence to recommend which partnerships to pursue, which terms are worth fighting for, and when to walk away - Outstanding communication skills with executive presence;
Infrastructure Security Engineer
ABOUT US: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable https://modal.com/blog/lovable-case-study, Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C https://modal.com/blog/modal-series-c at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We’re looking for an Infrastructure Security Engineer to design and secure the core systems that power our platform. This role focuses on building security directly into our infrastructure—from container isolation and orchestration to identity and secrets management in a multi-tenant, cloud-native environment. You’ll work closely with engineering teams to define secure primitives and ensure our platform is resilient, scalable, and trustworthy by design. This is a hands-on, deeply technical role focused on real systems, not compliance or policy. WHAT YOU'LL DO: Platform & Runtime Security - Design and improve isolation mechanisms for multi-tenant workloads (containers, sandboxing, execution environments) - Strengthen boundaries between customers, workloads, and internal systems - Identify and mitigate risks in distributed, dynamic compute environments Container & Orchestration Security - Secure and harden containerized workloads and orchestration systems (e.g., Kubernetes or similar) - Improve workload isolation, scheduling boundaries, and runtime protections - Evaluate tradeoffs in multi-tenant execution models Identity & Access Management - Design and improve authentication and authorization systems across services - Implement strong service-to-service identity and least-privilege access patterns - Improve access controls across infrastructure and internal systems Secrets & Key Management - Build and maintain systems for securely managing secrets, tokens, and credentials - Improve rotation, auditing, and access controls - Reduce secret sprawl and integrate secure patterns into developer workflows Cloud & Infrastructure Security - Secure cloud environments across providers (AWS, GCP, etc.) with a focus on consistency and portability - Improve network boundaries, service segmentation, and access controls - Embed security into infrastructure-as-code and deployment systems Engineering Partnership - Work closely with product and infrastructure teams to design secure systems from the ground up - Review architecture and code for security risks and provide actionable guidance - Identify patterns in risks and drive cross-cutting improvements REQUIREMENTS: Core Experience - Experience securing cloud-native infrastructure and distributed systems in production - Background in infrastructure, backend, or security engineering - Experience working in multi-tenant or high-scale environments Technical Depth - Strong understanding of containerization and orchestration systems (e.g., Kubernetes or similar) - Experience designing or securing isolation mechanisms in multi-tenant systems - Solid understanding of authenticat
Member of Creative Studio (Motion Designer)
ABOUT THE ROLE We're looking for a Senior Motion Designer to own motion graphics and GTM video output across Perplexity's social channels. Video is one of our most important channels for telling the Perplexity story, and we want someone whose primary focus is producing a steady stream of high-quality, on-brand motion work that performs. This is a video-production-first role. You'll spend most of your time concepting, animating, and shipping GTM materials for social — fast, polished, and distinctly Perplexity. In a secondary capacity, you'll help define our motion principles and contribute to broader creative technologist work as our motion practice matures. You'll report into the Brand/Creative Studio team and work closely with Brand, Growth, Comms, and the Producer to keep the pipeline moving. WHAT YOU'LL DO - Own the creation of motion graphics and video content for our social channels — concepting, storyboarding, animating, and delivering GTM materials end-to-end - Make video production your primary focus: a consistent, high-volume output of polished, on-brand motion work - Bring ideas to life across 2D and (where relevant) 3D, from styleframes and animatics to final delivery - Partner with Brand and Growth to turn launches and campaigns into motion that lands on social - Contribute to Perplexity's motion principles, systems, and templates so motion scales consistently across the team (secondary focus) - Contribute to broader creative technologist explorations — new tools, techniques, and AI-assisted workflows (secondary focus) - Collaborate with the Producer on scoping, scheduling, and delivering work on time WHAT WE'RE LOOKING FOR - Senior-level experience in motion graphics and animation, with video production as your core craft - A strong portfolio of expressive motion work — especially social, campaign, and GTM content that demonstrates range and polish - Deep command of animation fundamentals: timing, spacing, composition, visual rhythm, and design sensibility - Expert proficiency in After Effects and the broader Adobe Creative Suite; comfort in Figma - Ability to work fast, manage multiple deliverables, and iterate quickly in a high-output environment - A strong sense of when motion adds clarity or emotion — and when a still is the better choice NICE TO HAVE - Experience developing motion principles, systems, or toolkits that scale across a team - Comfort across 2D and 3D, plus compositing, post-production, and optimization for different social platforms - Creative technologist instincts — building or experimenting with tools and AI-assisted motion workflows - Graphic design fluency (layout, hierarchy, type) sufficient to build and adapt assets directly
Solutions Engineer, Enterprise
Scale plays a vital role in the development of AI applications. Our customer base is growing exponentially, and you will be on the front lines, ensuring that the world's most innovative companies become passionate, lifelong Scale customers. Solutions Engineers partner closely with AEs, Product, and MLEs to lead prospective customers through pre-sales, delivering customized demos and pilots to secure the “technical win”. Solutions Engineers scope customer technical requirements and develop an actionable SOW. They will work closely with the delivery team to help with initial implementation. Solutions Engineers are relentlessly curious about customer needs and pain points. They employ their expert Scale product knowledge and GenAI knowledge to design solutions that best address these needs. Solutions Engineers are strong relationship builders, great project managers, and provide technical expertise. You will: - Partner with Scale AEs on the customer journey, delivering tailored demos and prototypes according to the customer's requirements. - Develop technical domain expertise in Generative AI / large language model applications for Enterprise use cases, including customers in financial services, insurance, SaaS, and similar enterprises. - Be accountable for securing the “technical win” by unblocking technical challenges - Interact with customers daily to understand their needs and design solutions to better serve them. - Design and develop “Scopes of Work” by breaking down customer challenges into a project plan - Work closely with forward-deployed Software and Machine learning Engineers to develop agents in the initial post-sales stage - Work with AEs and PMs to identify customer-specific feature requests. - Drive strategic initiatives to improve the efficiency and effectiveness of the Solution Engineering team. Ideally, you'd have: - Strong engineering background with prior experience working with clients in a pre or post-sales capacity to realize business goals. - Prior experience developing with Python, Java and/or other web development languages. - Experience working in enterprise SaaS, cloud tech, finance, fintech or similar industries in a technical capacity with end-customer engagement. - A track record as a self-starter, motivated to independently unblock technical issues in the field with the customer, away from the mothership. - Presentation skills with a high degree of technical credibility when speaking with executives and front-line engineers. - High level of comfort communicating effectively across internal and external organizations. - Intellectual curiosity, empathy, and ability to operate with high velocity. Nice to haves: - GenAI Experience - Forward deployed engineering experience - Machine Learning Experience Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equ
Software Engineer (Backend), Enterprise
At Scale AI, we’re not just building AI tools—we’re pioneering the next era of enterprise AI. As businesses race to harness the power of Generative AI, Scale is at the forefront, delivering cutting-edge solutions that transform workflows, automate complex processes, and drive unparalleled efficiency for the largest enterprises. Our Scale Generative AI Platform (SGP) provides foundational services and APIs, enabling businesses to seamlessly integrate AI into their operations at production scale. We’re looking for a Backend Engineer to help bring large-scale GenAI systems to production. In this role, you’ll build the core infrastructure that powers AI products for some of the world’s largest enterprises—designing scalable APIs, distributed data systems, and robust deployment pipelines that enable production-grade reliability and performance. This is a rare opportunity to be at the center of the GenAI revolution, solving hard backend and infrastructure challenges that make AI truly work at enterprise scale. If you're excited about shaping how AI systems are deployed and scaled in the real world, we want to hear from you. At Scale, we don’t just follow AI advancements — we lead them. Backed by deep expertise in data, infrastructure, and model deployment, we are uniquely positioned to solve the hardest problems in AI adoption. Join us in shaping the future of enterprise AI, where your work will directly impact how businesses operate, innovate, and grow in the age of GenAI. You Will: - Design, build, and scale backend systems that power enterprise GenAI products, focusing on reliability, performance, and deployment across both Scale’s and customers’ infrastructure. - Develop core services and APIs that integrate AI models and enterprise data sources securely and efficiently, enabling production-scale AI adoption. - Architect scalable distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads. - Optimize backend performance for latency, throughput, and cost—ensuring AI applications can operate at enterprise scale across hybrid and multi-cloud environments. - Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security for large-scale AI deployments. - Collaborate with ML and product teams to bring cutting-edge GenAI models into production through efficient APIs, model serving systems, and evaluation frameworks. - Continuously improve reliability and scalability , applying strong engineering practices to make AI systems robust, maintainable, and enterprise-ready. Ideally, You Have: - 4+ years of experience developing large-scale backend or infrastructure systems, with a strong emphasis on distributed services, reliability, and scalability. - Proficiency in Python or TypeScript , with experience designing high-performance APIs and backend architectures using frameworks such as FastAPI, Flask, Express, or NestJS. - Deep familiarity with cloud infrastructure (AWS and Azure preferred), including container orchestration (Kubernetes, Docker) and Infrastructure-as-Code tools like Terraform. - Experience managing data systems such as relational and NoSQL databases (PostgreSQL, DynamoDB, etc.) and building pipelines for data-intensive app
Research Engineer, Machine Learning (RL Velocity)
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run. Responsibilities - Build and improve the RL training infrastructure that researchers depend on day-to-day - Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed - Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster - Own the reliability and performance of research runs end-to-end - Contribute to design decisions that shape how Anthropic does RL at scale You may be a good fit if you - Have strong software engineering fundamentals and a track record of building performant, reliable systems - Have worked on ML infrastructure, distributed systems, or research tooling - Care about enabling other people's work and find leverage through platforms rather than individual experiments - Are comfortable operating across the stack, from low-level performance work to RL algorithms - Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego Strong candidates may also have - Experience with large-scale distributed training (RL, pre-training, or post-training) - Familiarity with JAX, PyTorch, or similar ML frameworks - A track record of operating at the edge of research and infra in a fast-moving environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 - $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: </strong&
Customer Success Manager, Scaled
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As Anthropic scales its customer base across Claude Enterprise, Claude Code, and our API, we need to extend world-class customer success to a broader segment of customers through innovative, scalable approaches. The Scaled CSM will pioneer digital-first and one-to-many customer engagements that drive adoption, stickiness, retention, and expansion at scale. This role sits at the intersection of Customer Success innovation and AI transformation. As a Scaled Customer Success Manager at Anthropic, you'll be owning the success of a large portfolio of Commercial and Enterprise customers, you’ll design and execute scalable customer journeys through digital touch points, automated programs, one-to-many engagements, and strategic human intervention. You won't just manage customers — you'll "Claudify" the customer experience by building AI-powered processes that transform how customers adopt and derive value from Claude. Your work will directly shape how we engage customers at scale while maintaining the personalized, high-value experience that defines Anthropic. You'll collaborate closely with our Programmatic Success team to develop compelling customer content, with Sales organization to co-develop strategic plans, ensure seamless handoffs, and drive growth opportunities, with Product to channel customer insights and build consumption-driving features, and with Customer Success leadership to continuously optimize our scaled engagement model, all while pioneering how we leverage our own AI capabilities to transform digital customer engagement. Responsibilities: - Own scaled customer engagement for a large portfolio of Commercial and Enterprise accounts, managing customers through timebound, digital-first touchpoints that drive activation, consumption, retention, and expansion across Claude Enterprise, Claude Code, and API products - Execute timebound strategic human touchpoints at key moments— customer activation, expansion discussions, renewal conversations, risk interventions - ensuring high-impact interactions when customers need them most - Provide technical guidance. Develop deep product expertise to guide implementation decisions, advise on safe, impactful adoption of new features, , and translate AI capabilities into business value for audiences from developers to executives - Channel customer voice back to Product and leadership by aggregating insights from digital interactions, surveys, and community engagement to influence roadmap and improve customer experience - Partner cross-functionally with Marketing on customer campaigns, Sales on handoffs and growth, Product on adoption-driving features, and Customer Success on playbook development and optimization - Triage and prioritize across a pooled book. Work from a shared queue of engagement requests across a large customer pool. Ramp quickly on unfamiliar accounts, ruthlessly prioritize through a business-impact lens, and maintain quality across high concurrent volume.<
Technical Specialist, Claude Code
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic launches products at lightning speed and many of them grow at an unprecedented pace, too. For no product is this more true than Claude Code, the fastest-growing software product in history. That said, speed of adoption is not the same as depth of adoption. We’re building a team of Technical Specialists to drive meaningful adoption breadth and depth in our most strategic customers. We’ll do this through delivery of high-quality technical engagement and enablement in the customer’s ~ 90 days before and after contract signature. As a Technical Specialist, you’ll largely engage with customers post-sale. Once an account’s implementation set-up is complete, you’ll convert bottom-up developer passion into org-wide meaningful adoption through bespoke enablement tailored to the customer's stack, repos, and workflows and focused upon deep adoption of proprietary Claude capabilities, which we know drive stickiness. You'll also engage in strategic pilots before signature — partnering with Sales, Applied AI, and the customer's engineering leads to scope the pilot, run the enablement, and instrument the success criteria that close the deal. Carrying that context from pilot into post-sale is what makes adoption stick. This is not a technical implementation role — that work sits with our Implementation Specialists. You'll spend your time in front of developers launching Claude Code, department leaders adopting Cowork, on stage at customer events and Anthropic builder summits, and in Claude Code and Cowork, building the demo apps and reference implementations that prove what's possible. You’re the kind of person engineers want to grab coffee with after your workshops — credible because you can open a terminal in the meeting and actually drive the tool, exciting because you've thought hard about how agentic AI changes how software gets built, and useful because you can answer the next three questions a senior platform engineer is about to ask about security, scale, or agent behavior. What You'll Do: Drive end-user excitement inside enterprise accounts (primary focus) - Design and deliver customer-specific enablement programs — workshops, office hours, "build your first agent" labs, role-based curricula for engineering, data, platform, security, and knowledge-worker audiences - Drive deep adoption of proprietary Claude Code capabilities that make our tools sticky (subagents, hooks, MCP servers, headless mode, managed settings) tailored to the customer's stack, repos, and actual workflows (CI/CD, IDE integration, source control, secure coding, agentic pipelines) - Enable and excite champions and AI Center of Excellence leads inside customer orgs, arming them to scale the motion without you in the room Support strategic pilots with pre-sales technical enablement - Partner with Account Executives, Applied AI, and customer engineering leads on pilots for strategic accounts - Carry pilot context into post-sale engagement so the customer’s experi
Performance Engineer, GPU
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency. Working at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization. Strong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers. You might be a good fit if you: - Have deep experience with GPU programming and optimization at scale - Are impact-driven, passionate about delivering measurable performance breakthroughs - Can navigate complex systems from hardware interfaces to high-level ML frameworks - Enjoy collaborative problem-solving and pair programming - Want to work on state-of-the-art language models with real-world impact - Care about the societal impacts of your work - Thrive in ambiguous environments where you define the path forward Strong candidates may also have experience with: - GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization - ML Compilers & Frameworks: PyTorch/JAX internals, torch.compile, XLA, custom operators - Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight - Distributed Systems: NCCL, NVLink, collective communication, model parallelism - Low-Precision: INT8/FP8 quantization, mixed-precision techniques - Production Systems: Large-scale training infrastructure, fault tolerance, cluster orchestration Representative projects: - Co-design attention mechanisms and algorithms for next-generation hardware architectures - Develop custom kernels for emerging quantization formats and mixed-precision techniques - Design distributed communication strategies for multi-node GPU clusters - Optimize end-to-end training and inference pipelines for frontier language models - Build performance modeling frameworks to predict and optimize GPU utilization - Implement kernel fusion strategies to minimize memory bandwidth bottlenecks - Create resilient systems for planet-scale distributed training infrastructure - Profile and eliminate performance bottlenecks in production serving infrastructure - Partner with hardware vendors to influence future accelerator
ML Research Engineer, ML Systems
Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-... Observed freshness date: 2026-08-04T01:04:09-04:00 Freshness signal: first_party_updated_at Remote signal: unknown Salary: not published Canonical apply URL: https://job-boards.greenhouse.io/scaleai/jobs/4534631005 Source URL: https://job-boards.greenhouse.io/scaleai
Software Engineer, Robotics
Scale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems. You Will: - Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets - Build ML training and fine-tuning pipelines using Scale's robotics data - Work across backend (Python, Node.js, C++), and frontend (React, TypeScript) stacks to build end-to-end solutions - Develop tools and real-time systems for robotics data collection, teleoperation, model evaluation, data curation, and data annotation - Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development - Design comprehensive monitoring and evaluation frameworks for robotics models and data quality - Solving complex, late-stage industry challenges in concurrent and real-time robotic systems, with strict attention to timing constraints and data integrity. This often involves deep investigation, reviewing academic papers, and direct collaboration with robotics vendors - Collaborate with ML engineers and researchers to bring robotics research into production - Deliver features at high velocity while maintaining system reliability and performance Ideally, You Have: - 3+ years of high-proficiency software engineering experience, with a strong background in complex systems and the ability to independently research, analyze, and unblock hard technical problems. - Strong programming skills in Python and TypeScript/Node.js for production systems - Experience with React and modern frontend development for 3D interfaces - Concurrent and real-time systems, with special attention to timing constraints - Understanding of distributed systems, workflow orchestration, and cloud infrastructure (AWS, Temporal, Kubernetes, Docker) - Experience with databases (MongoDB, PostgreSQL) and data processing at large scale - Track record of working with cross-functional teams including ML engineers, researchers, and customers - Strong communication skills and ability to operate with high autonomy Nice to Haves: - Experience with C++ - Experience with robotics hardware platforms (robotic arms, mobile robots, perception systems) with a focus on time synchronization - Background in computer vision, SLAM, motion planning, or imitation learning - Familiarity with autonomous vehicle data, lidar technologies, or 3D data processing - Experience with ML model deployment and serving frameworks - Knowledge of teleoperation systems (ALOHA, UMI, hand tracking) or VR interfaces - Experience with workflow orchestration systems (Temporal, Airflow) - Published research or open-source contributions in robotics or autonomous systems PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. Th
Software Engineer, Platform
Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: - Own large new areas within our product, driving features from design through production deployment. - Work across backend, frontend, and interacting with LLMs and ML models - Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. - Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. - Deliver experiments and new features quickly, maintaining high quality and tight feedback loops with customers. - Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. - Adapt quickly—learning new technologies, frameworks, and tools as needed across the stack. Ideally you'd have: - 4+ years of full-time engineering experience, post-graduation - Strong experience in Python or Javascript/Typescript - Experience scaling or shipping products at high-growth startups. - Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). - Proficiency with SQL and modern API development. - Experience with Kubernetes, containerization, and microservice architectures. - Experience working with at least one major cloud provider (AWS, GCP, or Azure). PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the a
Finance Systems Engineer, Revenue
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Finance Systems team builds and owns the infrastructure that powers our quote-to-cash lifecycle—from pricing and billing through revenue recognition and financial close. As our revenue model grows in complexity, the team is moving beyond configuring off-the-shelf platforms and into building homegrown, production-grade financial applications that no vendor has built for us yet. We are seeking a Finance Systems Engineer to join our Finance Systems team in San Francisco. In this hands-on engineering role, you will both configure and extend the third-party platforms that run our financial operations including Zuora, Stripe, and Tesorio and design, build, and own full-stack applications and integrations that sit on top of them. You will write production Python, Node.js, and React code, author Workato recipes and API integrations across our SaaS stack, administer and tune the systems themselves, and ship working software—not manage vendors or write requirements documents. You will work at the intersection of software engineering and finance, building and configuring the tools that allow our Accounting, Revenue Operations, and Order Management teams to operate efficiently, accurately, and in compliance with SOX and ASC 606 requirements. The first thing you will inherit is our homegrown ledger application and the integrations that connect it to Workday, NetSuite, Zuora, Stripe, Tesorio, and Salesforce. From there, you will help us build the next generation of Finance tooling: self-serve workflows, automated reconciliation, and the operational surfaces that let Finance move at the speed the business demands. If you thrive in fast-paced environments and enjoy building scalable financial infrastructure from the ground up, come join us in our mission to build safe, transformative AI. Responsibilities - Own the architecture, development, and maintenance of Anthropic's internal finance applications, and own the configuration and ongoing administration of third-party platforms such as Zuora, Workday, and Tesorio - Build and maintain integrations across the Finance systems stack: Zuora, Stripe, Workday, NetSuite, Salesforce, Tesorio, BigQuery and Billing applications - Design system integrations that are auditable, observable, and recoverable—with the rigor that SOX compliance demands - Identify manual, error-prone workflows in the month-end close and automate them with tested, production-grade solutions - Partner with Accounting, Revenue Operations, and Order Management teams to translate business requirements into scalable technical designs—and then build them yourself - Develop and maintain technical documentation, data flow diagrams, and runbooks so the team can operate systems without engineering dependency - Contribute to continuous delivery infrastructure so Finance systems can ship reliably and frequently - Instrument the Finance systems stack with observability tooling so the team knows when a pipeline breaks before the accountants do - Become the go-to domain expert f
Data Scientist, GTM
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As part of our growing Data Science & Analytics team, you will play an instrumental role in Anthropic's mission of building safe and beneficial AI — this time by driving data-informed decisions across the commercial customer lifecycle. This role sits at the intersection of fast-moving sales operations and rigorous statistical analysis. You will work across multiple segments and products, partnering with analytics engineers, fellow data scientists, and go-to-market leadership to turn complex commercial data into actionable strategy. You will own measurement and analysis for new logo acquisition through activation, expansion, and retention for a rapidly scaling, consumption-based AI platform. You've worked in cultures of analytical rigor before, and you're eager to help shape the norms and best practices of a growing data science function at a pivotal moment in the company's growth. Key responsibilities - Define key metrics, build measurement frameworks, and maintain core reporting to evaluate GTM success across segments and products - Analyze commercial and user data to surface actionable insights, size opportunities, and influence roadmaps and go-to-market strategy - Develop hypotheses and apply rigorous causal inference methods — controlled experiments, synthetic controls — to make clear, actionable recommendations - Investigate anomalies, conduct root cause analyses, and provide data-driven guidance on priorities and decisions - Build statistical models, optimization frameworks, and simulations to support and automate commercial decision-making processes - Present analyses and recommendations to both technical and non-technical stakeholders, including GTM leadership - Establish foundational data practices and help scale analytics infrastructure to support rapid product and commercial iteration Minimum qualifications - Proficiency in Python, SQL, and data visualization tools - Expertise in experimental design, causal inf
Research Engineer, Chip Design RL (Reinforcement L...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the RL teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Fable 5 and Opus 4.8. Our work spans several key areas: - Developing systems that enable models to use computers effectively - Advancing code generation through reinforcement learning - Pioneering fundamental RL research for large language models - Building scalable RL infrastructure and training methodologies - Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the role We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to design silicon. Hardware design is difficult and unforgiving – exactly the sort of domain we want Claude to excel at. You'll leverage your chip design expertise and turn it into tasks and signals for models to learn from. Specifically, you will: - Invent, design, and implement RL environments and evaluations for agentic RTL generation, design (including formal) verification, physical design optimization. - Work on cross-cutting RL considerations such as EDA-tool latency optimization and proxy rewards. - Conduct experiments and shape our roadmap. - Deliver your work into research and production training runs. - Collaborate with other researchers and engineers across and outside Anthropic. You may be a good fit if you: - Have expertise in ASIC or FPGA design: RTL, design verification (UVM, formal methods, coverage-driven), physical design (synthesis, place-and-route, timing closure), PPA optimization, DFT, ECOs. - Are fluent with industry EDA tools and processes. - Have taped out chips and have experience going from spec to silicon. - Know how to balance research exploration with engineering implementation. - Are passionate about AI's potential and committed to developing safe and beneficial systems. Strong candidates may also have: - Experience with reinforcement learning, evaluations or environments. - Built tooling or automation around chip design flows. - Worked on ML accelerators or high-performance compute hardware. - Familiarity with high-level synthesis or architecture simulators. </ul&
People Research Scientist, Recruiting
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking a Recruiting Research Scientist to join our People Data Solutions team. You’ll be the research expert supporting our Recruiting organization, using rigorous scientific methods to advance our understanding of recruiting funnels, interview effectiveness, candidate experience, and recruiting capacity. This role sits at the intersection of organizational science, behavioral research, and people strategy – developing novel frameworks and conducting systematic research that drives evidence-based people decisions across our growing organization. This role offers the opportunity to make a significant impact on both our recruiting practices and the broader field of people science at a leading AI safety company. Responsibilities Research design & scientific inquiry - Design and execute systematic research studies to answer fundamental questions about recruiting funnel health, assessment quality, candidate experience, and quality of hire - Generate and test hypotheses about sourcing strategies, interview design, and selection decisions using rigorous experimental and quasi-experimental methods - Conduct mixed-method research to understand what are the drivers and blockers to recruiting operations. - Navigate research ethics considerations when studying candidate data, ensuring responsible research practices Selection & assessment research - Design and execute validation studies to assess the quality of interviews and other selection tools - Utilize psychometric techniques to analyze and improve interviewer calibration and rating consistency - Lead investigative research into innovative approaches for candidate assessment Metrics design and governance - Design the metrics framework for recruiting org health — defining the canonical KPIs, dimensions, and definitions that leadership uses to understand funnel performance, capacity, and hiring quality - Establish the governance and definitional rigor that keeps metrics consistent across tools and reporting surfaces Analytical solution building - Architect analytical solutions that convert research insights into actionable products, empowering stakeholders to execute data-driven scenario and strategic planning - Quantify the adoption and downstream impact of deployed tools, driving iterative improvements Visualization & communication - Build compelling visualizations and dashboards that make complex research findings accessible to diverse audiences - Present research findings to senior leadership with clear, actionable recommendatio
Engineering Manager, MLE
About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: - Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. - Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. - Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. - Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. - Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large. You might thrive in this role if you: - Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field. - Demonstrated experience in deep learning and transformers models - Experience with content understanding or abuse prevention with LLMs is a plus - Proficiency in frameworks like PyTorch or Tensorflow - Strong foundation in data structures, algorithms, and software engineering principles. - Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization - Excellent problem-solving and analytical skills, with a proactive approach to challenges. - Ability to work collaboratively with cross-functional teams. - Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines - Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Software Engineer (ML/Game Development)
About the company: Located in Redondo Beach, CA, GungHo Online Entertainment America Inc. is the U.S. subsidiary of the Japanese game company GungHo Online Entertainment, Inc. Publishing titles across multiple platforms ranging from console to handheld and mobile, our group is comprised of veterans from various aspects of the industry brought together by one simple thing: a love of gaming. Position Summary: This position is responsible for designing, finetuning, and shipping machine learning and generative AI features for our new, internally developed game, as well as general debugging and troubleshooting. You will work at the intersection of applied ML and game development. What you will be doing: - Design, implement, and debug ML/AI-driven features for our internally developed game, with a focus on LLM-powered NPC dialogue and model infrastructure. - Finetune, evaluate, and optimize models for in-game use, balancing quality against latency, memory, and cost. - Build and maintain inference systems and data pipelines that integrate cleanly with the game engine and runtime. - Contribute to gameplay features and general game code alongside your ML work. This is a hands-on role on both sides. - Ship other generative AI features as the game evolves. - Discuss, design, and plan AI features with artists, game designers, and gameplay engineers. - Test prototypes of future titles and AI systems to provide constructive feedback. - Attend industry conventions and live events as needed. Qualifications: - 4 years experience in programing, professionally or in school is a plus. - B.S. or equivalent in Computer Science is preferred. - C++ and game-engine experience (Unreal) is a huge plus - Demonstrated hands-on experience finetuning or deploying ML models. Whether through professional work, personal projects, or self-directed experimentation. We're looking for hands-on ML experience outside of coursework. - Solid general programming proficiency (any language); comfortable working in a production codebase. - No specific stack required — we care more about what you have actually built than which tools you used. - Experience deploying models for low-latency, real-time inference is a plus. - Familiarity with 3D graphics, shaders, or GPU programming is a plus. - Strong communication skills. - Desire to learn and to grow, including into the game-development side. - Ability to work in small, agile team environments. - Passion for narrative games Why you want to work here: At GungHo, we’re enthusiastic about creating fun games and we’re always looking for talented individuals with whom we can share our passion. We have a highly collaborative culture where everyone wants to work together to get things done! Perks: - 100% employer-paid insurances: Health Insurance (PPO Medical, Dental, and Vision), Life Insurance, Accidental Death and Dismemberment insurance, and Long Term Disability Insurance - 401(k) with employer match - Competitive paid time off: Vacation, Personal time, Sick Leave, Holidays, and Winter Breaks. - An incentive may be provided based on business performance. Business Hours: 10:00 AM - 7:00 PM in Pacific Time Salary Range: $75,000 - $119,000 per year (DOE) <span style="fon
Product Security Engineer, Public Sector
We are seeking a highly technical Product Security Engineer to join our Public Sector Infrastructure & Security team. Our Product Security Engineers ensure the security and integrity of our products and services. You will conduct in-depth code reviews, implement security best practices, and influence the overall security strategy. Your expertise in TypeScript, Python, Kubernetes, CI/CD, SAST, DAST, and terraform orchestration will be crucial in identifying and mitigating potential security vulnerabilities. You will also structure complex problems, diagnose root causes independently, and clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact. You will: - Conduct in-depth code reviews to identify and remediate security vulnerabilities. - Evaluate and enhance the security of our product offerings, through RFC and service review. - Implement and maintain CI/CD pipelines with a strong focus on security. - Perform Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) to identify vulnerabilities in production code. - Utilize terraform orchestration to ensure secure and efficient infrastructure management. - Guide engineering teams to build robust long-term solutions that consider security and privacy. - Clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact. - Influence the security strategy and direction of the team, advocating for best practices and continuous improvement. Ideally, you’d have: - at least a Secret level government security clearance - Proven experience as a Security Engineer with a focus on product security. - Proficiency in NodeJS, TypeScript, Python, and/or Kubernetes. - Strong understanding of modern Javascript application design. - Production experience with Kubernetes backed services - Hands-on experience with SAST and DAST tools and methodologies. - Familiarity with terraform orchestration for infrastructure management. - You can structure complex problems and diagnose root causes independently, providing actionable insights without requiring manager input. - Excellent communication skills, with the ability to clearly present technical concepts and their implications to both technical and non-technical stakeholders. - Demonstrated ability to influence security strategies and drive improvements within a team. - Relevant security certifications (e.g., CISSP, CEH, OSCP) are a plus. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision cover
AI Product Engineer, Games
We believe AI will fundamentally change how games are built and played, from content creation to player experience, and we’re building at the frontier of that shift. Puzzle Cats builds casual mobile games played by tens of millions of people worldwide. We’re a small, high-performing team that moves faster than most studios think is possible, taking games from concept to App Store quickly and continuously iterating on live games with millions of active players. We’re looking for an AI Product Engineer who wants to build something big and move fast. This is a hands-on, highly product-oriented role for someone who wants to invent, ship, and scale AI-native game experiences. You’ll work across the full development process, from prototype to production, collaborating with designers, engineers, and product teams to launch new games and improve live ones. Features you build can reach millions of players within weeks. We’re especially interested in engineers who don’t just tolerate AI tools, they live inside them. Someone who naturally uses tools like Claude, Cursor, OpenAI, or coding agents as part of how they build, understands the code they generate, and knows when to prompt a solution versus writing it from scratch. You’ll own features end-to-end, from gameplay systems and backend infrastructure to analytics, building, shipping, measuring, and iterating quickly based on real player data. We ship fast, test aggressively, and aren’t afraid to kill ideas — including AI ones — if the data doesn’t support them. What You’ll Do - Use AI to create new player experiences that wouldn’t be possible otherwise - Build and ship mobile game features in Unity (C#) for iOS and Android, including gameplay mechanics, onboarding flows, monetization experiments, and live-ops systems - Prototype and launch new game ideas quickly, moving from concept to playable builds in weeks, not months - Design and build AI-powered gameplay and product features, including content generation, personalization, and AI-driven mechanics - Design and implement AI systems and pipelines, including RAG, embeddings, tool use, and agents - Optimize AI systems for cost, latency, and scalability, including token usage, caching, and model selection - Develop and maintain backend systems for live games, including leaderboards, events, A/B testing infrastructure, and cloud services (GCP/Firebase) - Collaborate closely with designers and analysts to interpret player data and turn insights into gameplay improvements - Own the full lifecycle of your features, including implementation, analytics instrumentation, debugging, and performance optimization - Review code and maintain high engineering standards, including AI-generated code Must-Haves - Strong problem-solving ability, a hacker mindset, and deep object-oriented programming knowledge - Ability to write clean, maintainable code and move quickly without sacrificing quality - Experience integrating real AI features into products, not just using AI tools, but shipping or meaningfully prototyping model-driven functionality - Experience integrating LLMs into production systems using OpenAI, Anthropic, or open-source models - Strong intuition for how LLMs behave, including prompt design, failure modes, and output quality - Experience building and iterating on AI features using real user data - 3+ years of production software engineering experience, ideally with shipped mobile apps or games built in Unity (C#) for iOS and Android - Experience with Python or JavaScript, cloud infrastructure/back-end systems, and Git - Ability to analyze player data and metrics to improve gameplay and product decisions - Strong critic
Staff Software Engineer - GenAI inference
P-1285 About This Role As a staff software engineer for GenAI inference, you will lead the architecture, development, and optimization of the inference engine that powers Databricks Foundation Model API.. You’ll bridge research advances and production demands, ensuring high throughput, low latency, and robust scaling. Your work will encompass the full GenAI inference stack: kernels, runtimes, orchestration, memory, and integration with frameworks and orchestration systems. What You Will Do Own and drive the architecture, design, and implementation of the inference engine, and collaborate on model-serving stack optimized for large-scale LLMs inference Partner closely with researchers to bring new model architectures or features (sparsity, activation compression, mixture-of-experts) into the engine Lead the end-to-end optimization for latency, throughput, memory efficiency, and hardware utilization across GPUs, and accelerators Define and guide standards to build and maintain instrumentation, profiling, and tracing tooling to uncover bottlenecks and guide optimizations Architect scalab... Observed freshness date: 2026-07-24T19:28:51-04:00 Freshness signal: first_party_updated_at Remote signal: unknown Salary: not published Canonical apply URL: https://databricks.com/company/careers/open-positions/job?gh_jid=8202698002 Source URL: https://job-boards.greenhouse.io/databricks
Staff Software Engineer - Machine Learning (Search...
P-1408 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products . Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2025, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and i... Observed freshness date: 2026-07-24T19:28:49-04:00 Freshness signal: first_party_updated_at Remote signal: unknown Salary: not published Canonical apply URL: https://databricks.com/company/careers/open-positions/job?gh_jid=7958982002 Source URL: https://job-boards.greenhouse.io/databricks
LLM Inference Frameworks and Optimization Engineer
About the Role At Together.ai, we are building state-of-the-art infrastructure to enable efficient and scalable inference for large language models (LLMs). Our mission is to optimize inference frameworks, algorithms, and infrastructure, pushing the boundaries of performance, scalability, and cost-efficiency. We are seeking an Inference Frameworks and Optimization Engineer to design, develop, and optimize distributed inference engines that support multimodal and language models at scale. This role will focus on low-latency, high-throughput inference, GPU/accelerator optimizations, and software-hardware co-design, ensuring efficient large-scale deployment of LLMs and vision models. This role offers a unique opportunity to shape the future of LLM inference infrastructure, ensuring scalable, high-performance AI deployment across a diverse range of applications. If you're passionate about pushing the boundaries of AI inference, we’d love to hear from you! Responsibilities Inference Framework Development and Optimization Design and develop fault-tolerant, high-concurrency distributed infer... Observed freshness date: 2026-07-10T19:42:34-04:00 Freshness signal: first_party_updated_at Remote signal: unknown Salary: not published Canonical apply URL: https://job-boards.greenhouse.io/togetherai/jobs/4687884007 Source URL: https://job-boards.greenhouse.io/togetherai
Staff Machine Learning Engineer, Voice AI
About the Role Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability. We're looking for a Staff ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly. This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech. Own the model serving st... Observed freshness date: 2026-07-10T19:42:35-04:00 Freshness signal: first_party_updated_at Remote signal: unknown Salary: not published Canonical apply URL: https://job-boards.greenhouse.io/togetherai/jobs/5140763007 Source URL: https://job-boards.greenhouse.io/togetherai
Senior Machine Learning Engineer, Voice AI
About the Role Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability. We're looking for a Senior ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly. This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech. Own the model serving s... Observed freshness date: 2026-07-10T19:42:35-04:00 Freshness signal: first_party_updated_at Remote signal: unknown Salary: not published Canonical apply URL: https://job-boards.greenhouse.io/togetherai/jobs/5088817007 Source URL: https://job-boards.greenhouse.io/togetherai
Office Manager
ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE WORKPLACE & REAL ESTATE TEAM The Workplace & Real Estate team builds the places where LangChain builds the future of AI agents. Our job is to make every office somewhere people want to be — spaces that run flawlessly, feel great to walk into, and reflect the craft bar of the company in every detail. We treat the workplace as a product: designed with intent, measured, and continuously improved. We run a small, high-agency team of on-site owners in each hub, and we automate the manual work rather than adding it — across two master-lease hubs (SF, NY) and coworking spokes as the company scales. ABOUT THE ROLE The Office Manager owns our SF HQ end-to-end — both the on-the-ground experience and the systems that make it run. SF is our largest hub and headquarters, we hold the master lease, we're moving into new space, and we regularly host company and team offsites. You open and reset the space first thing every morning and are the face of the office through the day — and you build the tooling, standards, and vendor programs that keep it running consistently as we scale. This is a hands-on role for a builder who takes pride in a flawless space and in the systems behind it. Location: This role is based on-site in our San Francisco (HQ) office, five days per week. WHAT YOU'LL DO OWN THE SPACE & THE CRAFT BAR - Open and reset the space first thing every morning — before people arrive, the office is clean, stocked, and ready - Keep the space super organized, neat, tidy, clean, and stocked at all times; it should always be on point and represent the quality of the company - Run a regular walkthrough punch list and stay on top of the details — wires tucked, chairs in, nothing out of place BE THE FACE OF THE OFFICE - Present through business hours as front-of-house: greet guests, welcome and guide new hires and visitors, and be the person people find - Plan and run local in-office events, team moments, and the offsites hosted at HQ RUN OPERATIONS, VENDORS & BUDGET - Manage facilities, supplies, snacks, and equipment; own on-site vendor relationships (cleaning, food, maintenance); serve as primary contact for building management and repairs - Rationalize and manage vendor programs — move us off ad-hoc ordering to contracted, consistent programs - Own budget tracking for the office; help track cost-per-seat and utilization; partner with Finance BUILD THE SYSTEMS & STANDARDS - Own the workplace ticket queue in Console for your office and help build the shared SLA framework and resolution metrics - Deploy and own the workplace tech stack — desk booking, room scheduling, visitor management, mailroom/deliveries — partnering with IT on networking
AI Artist
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