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AI Solutions Engineer, Talent Acquisition
Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years. ABOUT THE TEAM The Talent Operations Systems team is responsible for the systems, data, process, and infrastructure that make Anduril's recruiting function work at scale. We work in a highly cross-functional manner, sitting between TA leadership, recruiters, business leaders, and the people data team to drive recruiting processes and systems and turn fragmented operational data into a trusted, decision-ready data product. Our work directly shapes how Anduril finds, evaluates, and hires the engineers, operators, and builders behind the future of defense, and it's how recruiting leadership knows where to invest, what's working, and where the funnel is breaking. ABOUT THE JOB We are looking for an AI Solutions Engineer, Talent Acquisition to join our rapidly growing TA Operations team. This role is embedded within the TA Team — and you will be the hands-on technical owner of AI and automation across Anduril's TA function. You will build AI agents and automations that solve concrete recruiting problems, improving efficacy and efficiency. You will use that to inform what gets built, what gets bought, and what doesn't get built at all. You will spend most of your time shipping — primarily on strategically prioritized projects, but also unblocking the team with home-grown ad hoc tools and quick-turn solutions. You will form a strong, defensible point of view on where AI and automation will drive value across the recruiting funnel, surface the highest-leverage opportunities, and lead build-vs.-buy assessments grounded in scalability, cost, safety, and compliance. You will own TA's AI and automation roadmap end-to-end — communicating progress and tradeoffs to TA leadership, giving regular read-outs, and partnering with our TA Enablement team to drive baseline AI literacy across the broader recruiting org. This will require strong applied AI engineering chops (LLMs, agentic workflows, tool use, retrieval, evals), real software engineering rigor (Python, APIs, integrations, version control, testing, deployment), and the judgment to ship pragmatic systems in a regulated environment. If you are someone who is energized by ambiguous problem spaces, who can sit with recruiters and sourcers to understand their friction before writing a line of code, who has strong opinions about when AI is the right tool and when it isn't, and who wants to own both the build and the strategy behind it, then this role is for you. WHAT YOU’LL DO - Build AI agents and automations that solve real recruiting problems — sourcing, screening, outreach, scheduling, candidate research, pipeline operations, reporting — with measurable ROI tied to recruiter time saved, funnel improvements, or hiring outcomes. - Own TA's AI and automation roadmap end-to-end — prioritization, sequencing, communication, and progress read-outs to TA leadership and stakeholders. - Partner closely with Anduril's Corporate Technology team to understand the company's AI tooling, model access, infrastructure, security posture, and roadmap — and design solutions that ride those rails rather than fight them. - Form and defend a clear point of view on where AI and automation will and won't drive value across the recruiting function, and proactively surface opportunities the team hasn't asked for yet. - Lead rigorous build-vs.-buy assessments — evaluating vendors, internal platforms, and custom builds against scalability, total cost, safety, compliance, and long-term maintainability. - Ship pragmatically — strategically prioritized initiatives most of the time, but also fast, home-grown solutions for ad hoc team requests when that's the rightcall. - Partner with the TA Enablement team to drive baseline AI literacy across the recruiting org — internal training, documentation, prompt patterns, guardrails, and best practices that recruiters and sourcers can actually use. - Own the safety, compliance, and governance posture of every AI and automation system you ship — PII handling, role-based access, audit trails, model risk, data residency, and ITAR/CUI considerations where applicable. - Define and instrument success metrics for every shipped system — adoption, time saved, quality, error rates, cost per outcome — and retire what isn’t working. - Establish lightweight engineering practices for the function — version control, testing, evals, deployment, monitoring — so AI work is durable rather than throwaway. REQUIRED QUALIFICATIONS - 4+ years of hands-on technical experience building production software, with at least 1–2 years of that focused on applied AI / LLM-based systems (agents, tool use, RAG, evaluations, automations). - Genuinely curious about the recruiting / TA domain (prior experience strongly preferred) — willing to sit with recruiters and sourcers, learn their workflows, and build for their problems rather than the most technically interesting ones. - Strong software engineering fundamentals — APIs and integrations, version control, testing, CI/CD, basic infrastructure, and deployment. - Production experience building AI agents or LLM-driven automations for use across a growing team (250+ people) — including prompt design, tool use, retrieval, evaluation, and the failure modes that come with non-deterministic systems. - Experience integrating with SaaS APIs and stitching workflows across multiple tools — comfort reading API docs, handling auth, rate limits, pagination, and webhooks. - Demonstrated ability to identify high-leverage opportunities in an operational function, ship working systems against them, and quantify the impact. - Strong build-vs.-buy judgment — can rigorously evaluate vendors and internal platforms against custom builds on scalability, cost, safety, compliance, and maintainability. - Comfortable owning a roadmap end-to-end — prioritization, communication to non-technical leadership, and clear written read-outs. - Strong written and verbal communication — can explain technical tradeoffs to recruiting leadership and translate fuzzy operational pain into specific technical scope. - Genuinely curious about the recruiting / TA domain — willing to sit with recruiters and sourcers, learn their workflows, and build for their problems rather than the most technically interesting ones. - Must be a U.S. Person due to required access to U.S. export controlled information or facilities PREFERRED QUALIFICATIONS - Prior experience embedded in or directly partnering with a Talent Acquisition, Recruiting Operations, or People function as the primary technical owner of AI / automation. - Familiarity with the modern recruiting stack — Greenhouse, Gem, LinkedIn Recruiter, Workday, scheduling tools, etc. — and the ways their data and workflows fit together. - Experience designing AI literacy programs, internal enablement, or hands-on training for non-technical end users. - Background in defense, aerospace, financial services, healthcare, or another regulated industry where compliance, PII handling, and auditability are first-class requirements. - Track record of retiring or replacing systems you previously shipped — strong taste for what to kill, and when to iterate, not just what to build. US Salary Range $129,000 - $171,000 USD The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including: Benefits At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits . Protecting Yourself from Recruitment Scams Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information. To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind: - No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates. - Please always verify communications: - Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address. - Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com . - Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links. - What to Do If You Suspect Fraud: Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to contact@anduril.com . Your proactive caution is invaluable in protecting your personal information and upholding the security and trustworthiness of our recruitment efforts. Data Privacy To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/ . By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.
SWE - Distributed
WHY ACHIRA - Join a world-class team of scientists, ML researchers, and engineers working together to reshape the future of drug discovery. - Work on cutting edge ML infrastructure at frontier scale: massive compute, massive data, and massive ambition. - Own impactful work end-to-end — from ideation to architecture to deployment on large-scale infrastructure. - Work in an environment that rewards rigor, speed, and a builder’s mindset. ABOUT THE ROLE Achira is building best-in-class foundation models to solve the most challenging problems in simulation for drug discovery and beyond. Atomistic Foundation simulation models (FSMs) as world models of the physical microcosm span machine learning interaction potentials (MLIPs), neural network potentials (NNPs), and diverse classes of generative models. We're seeking a Software Engineer passionate about distributed computing and its applications in machine learning. You'll have the opportunity to architect and build from the ground up the infrastructure for our ML data generation pipelines, model training, and fine-tuning workflows across large-scale distributed systems. Your expertise will ensure our compute clusters are efficient, observable, cost-effective, and reliable—helping us push the boundaries of ML development. If you're passionate about distributed systems, performance optimization, and cloud cost efficiency, we'd love to hear from you. You'll be empowered to eat, breathe, and think about the orchestration of complex workloads on multiple vendors scattered anywhere on the planet. Achira is a company which lives and breaths on computation, facile access at the lowest cost for our uniquely suited workloads is a mission critical endeavor. WHAT YOU’LL DO - Architect & Build: Design, implement, and optimize distributed compute infrastructure for ML data processing, training, and fine-tuning. - Optimize & Monitor: Improve cluster observability, scheduling, and resource utilization (CPU/GPU/TPU). - Compute Efficiency: Research and implement cost-efficient compute solutions (spot instances, auto-scaling, multi-cloud strategies). - Tooling: Develop tools for monitoring, debugging, and performance tuning of large-scale ML workloads. - Collaboration: Collaborate with ML engineers to accelerate training pipelines and reduce bottlenecks. - Innovation: Stay current with emerging technologies in distributed computing (e.g., Ray, Kubernetes, Spark, Slurm) and apply them strategically. ABOUT YOU - You are excited about and have lots of experience in building or working with distributed computing frameworks (e.g., Ray, Dask, Celery) - You have a good grasp of parallel computing, job scheduling, and resource management. - You're comfortable identifying and resolving performance issues in distributed systems (profiling, bottlenecks, network overhead) - You've implemented solutions using cloud compute platforms (AWS, GCP, Azure) and cluster orchestration (Kubernetes, Slurm) - You are familiar with popular ML frameworks (PyTorch, TensorFlow, or JAX) and MLOps best practices such as model deployment and GPU performance monitoring Eligibility In compliance with United States federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to provide required employment eligibility verification documentation upon hire.
Member of Clinical Staff
ABOUT ABRIDGE Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients. Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems. We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. THE ROLE Abridge is looking for Clinician Scientists to drive the development of our AI-powered clinician tools. We’re looking for someone who can combine deep clinical expertise with a background in AI. In this role, you will help shape AI-driven tools and ensure our models generate accurate, high-quality products that enhance clinician efficiency and patient care. You’ll work closely with engineers, researchers, product managers, and clinicians to refine AI models, validate outputs, and develop new capabilities that improve documentation workflows. Must be willing to work from our SF office at least 3x per week This position requires a commitment to a hybrid work model, with the expectation of coming into the office a minimum of three times per week. Relocation assistance is available for candidates willing to move to San Francisco. WHAT YOU’LL DO - Develop and refine AI-driven clinical tools across notes, risk adjustment (HCC capture), clinical decision support, and prior authorization using clinical expertise and prompt engineering - Define what “clinically meaningful” output looks like for each product area, including acceptable error rates, failure modes, and quality thresholds - Collaborate with cross-functional teams (engineers, data scientists, clinicians) to integrate medical insights into AI models. - Write, review, and optimize prompts to improve AI model performance in clinical contexts. - Build and refine evaluation tools to streamline medical documentation quality assessment, including hallucination detection, omission detection, and medication safety checks - Translate clinical needs into technical specifications and data models. - Define clinical guardrail metrics and baselines; own pre/post evaluation requirements for any model update that affects clinical output - Contribute to product development, revenue cycle management, and broader business initiatives - Monitor clinical guideline update cycles and flag when product behavior needs to evolve based on new standards or payer policies WHAT YOU’LL BRING - MD, PA, DO (or equivalent clinical degree) with direct experience working in clinical practice - Deep understanding of medical documentation, clinical workflows, and medical terminology - Ability to evaluate AI-generated clinical notes, provide structured feedback, and guide improvements - Strong knowledge of healthcare data standards (e.g., FHIR, HL7) and privacy regulations (e.g., HIPAA) - Hands-on experience in clinical data validation and quality assessment - Experience collaborating with engineers and product teams to build AI-powered clinical tools - Strong analytical and problem-solving skills - Excellent written and verbal communication skills NICE TO HAVE - Experience in software engineering, particularly in prompt engineering or AI model development - Python programming skills and experience with deep learning frameworks such as PyTorch, JAX, and/or TensorFlow - Previous experience in AI-powered clinical documentation tools or clinical decision support systems - Published research in AI, machine learning, or healthcare technology WHY WORK AT ABRIDGE? At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month. Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business. Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients. We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life. If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you. HOW WE TAKE CARE OF ABRIDGERS: - Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employees - Comprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families. - Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA. - Paid Parental Leave: Generous paid parental leave for all full-time employees. - Family Forming Benefits: Resources and financial support to help you build your family. - 401(k) Matching: Contribution matching to help invest in your future. - Personal Device Allowance: Tax free funds for personal device usage. - Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits. - Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more. - Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals. - Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment. - Compensation and Equity: Competitive compensation and equity grants for full time employees. - ... and much more! EQUAL OPPORTUNITY EMPLOYER Abridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability. We're committed to providing reasonable accommodations throughout the interview process. Once you submit your application, we'll follow up with details on how to request an accommodation for interviewing, completing any assessments, or otherwise participating in the selection process. STAYING SAFE - PROTECT YOURSELF FROM RECRUITMENT FRAUD We are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com http://abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article https://consumer.ftc.gov/consumer-alerts/2023/05/scammers-are-hijacking-job-ads-heres-how-spot-fakes. Please exercise caution and cease communications if something feels suspicious about your interactions.
Associate General Counsel, Product (Data Products,...
ABOUT ABRIDGE Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients. Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems. We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. THE ROLE As an Associate GC, Product (Data Products, Machine Learning, and AI), you'll play a pivotal role as the go-to legal advisor for the teams building Abridge's AI and machine learning models, products, and technologies. This role is highly cross-functional across Abridge with a focus on advising product teams on the cutting edge of AI model and product developments, from ambient clinical documentation to emerging agentic and multimodal healthcare experiences. This is a unique opportunity to work at the forefront of the legal, AI, and healthcare fields, shaping how a category-defining company navigates novel legal terrain. WHAT YOU'LL DO - Serve as go-to counsel and partner for teams building Abridge's core AI models and products, advising on legal issues that span model development, agentic workflows, multimodal outputs, and downstream clinical use. - Identify, address, and design practical mitigations for AI-specific legal risks, including model behavior, output accuracy, IP, data provenance and training rights, and liability for AI-generated content. - Develop and scale flexible legal processes, frameworks, and contract language suited to the pace of frontier AI development, rather than relying solely on precedent from other industries. - Serve as an internal expert on AI legal and policy matters, helping shape Abridge's positions on emerging AI regulation and representing those positions with external counsel, regulators, and industry groups as needed. - Support privacy impact assessments, model risk assessments, and data governance frameworks specific to AI training, fine-tuning, and deployment. - Partner with legal, product, and compliance stakeholders on AI principles such as transparency, accountability, and human oversight. WHAT YOU'LL BRING - Passion for Abridge's mission and the drive to support fast-moving AI product and research teams. - 12+ years of legal experience, including 6+ years counseling on AI, machine learning, or other emerging technology products. Prior in-house experience is required. - Creativity in navigating novel legal matters, including building new processes, language, and frameworks to meet the needs of a fast-moving company in an emerging industry. - Working knowledge of AI-specific legal issues, including IP and copyright in AI-generated content, training data rights, model liability, and responsible AI principles. - Proven ability to translate complex regulatory and technical AI concepts into clear, practical guidance for non-legal, technical audiences. - Comfort operating with ambiguity, tight timelines, and a high volume of novel legal questions with no settled precedent. - Strong sense of ownership, intellectual curiosity about technology, and sound judgment in ambiguous situations. BONUS POINTS IF… - You have prior in-house experience at a growth-stage AI or healthcare technology company. - You have a strong understanding of federal and state healthcare laws, including HIPAA and data privacy regulations, as applied to AI systems. This role is in San Francisco or New York City. Monday/Wednesday/Friday are in office days. WHY WORK AT ABRIDGE? At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month. Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business. Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients. We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life. If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you. HOW WE TAKE CARE OF ABRIDGERS: - Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employees - Comprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families. - Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA. - Paid Parental Leave: Generous paid parental leave for all full-time employees. - Family Forming Benefits: Resources and financial support to help you build your family. - 401(k) Matching: Contribution matching to help invest in your future. - Personal Device Allowance: Tax free funds for personal device usage. - Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits. - Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more. - Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals. - Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment. - Compensation and Equity: Competitive compensation and equity grants for full time employees. - ... and much more! EQUAL OPPORTUNITY EMPLOYER Abridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability. We're committed to providing reasonable accommodations throughout the interview process. Once you submit your application, we'll follow up with details on how to request an accommodation for interviewing, completing any assessments, or otherwise participating in the selection process. STAYING SAFE - PROTECT YOURSELF FROM RECRUITMENT FRAUD We are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com http://abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article https://consumer.ftc.gov/consumer-alerts/2023/05/scammers-are-hijacking-job-ads-heres-how-spot-fakes. Please exercise caution and cease communications if something feels suspicious about your interactions.
Senior Software Engineer, ML Platform
About Xaira Therapeutics Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London. About the Role We are seeking a Senior Software Engineer to join our Platform team to design, build, and deploy the AI infrastructure that powers our world-class research team. In this role, you’ll collaborate closely with AI Scientists and other engineers to enable the effective use of thousands of GPUs for training and inferencing cutting-edge biological foundation models. This role spans a range of problems and skillsets, ranging from MLOps of cutting-edge GPU clusters, to backend engineering of control plane APIs. Our ideal candidate has an opinion about slurm or kubernetes for model training, cares about maximizing bandwidth from the storage subsystems to the GPU, and can build the API paved path for submitting training jobs that are able to dispatch to multiple clusters. What You Will Do - Develop and improve our model training system, responsible for dispatching distributed training jobs to clusters across multiple clouds. - Deploy storage subsystems that improve dataset management and throughput for training datasets. - Build evaluation infrastructure that enables easy execution and tracking. - Build base tooling for integrating model training with other internal infrastructure, such as telemetry, experiment tracking, and checkpointing. - Prior experience with biology is not required - we will teach what you need to know. You’ll get to go in the lab, and for our ideal candidate, this should be a perk, not a chore! Preferred Skills and Qualifications - Degree in Computer Science, Machine Learning, Computational Biology, or a related field. - 5+ years of industry experience building and deploying ML systems in production environments - Experience leading technical projects and driving cross-functional execution. - Strong programming skills in Python. - Experience with infrastructure/ops tools such as Terraform, Ansible. - Experience with deep learning frameworks such as Torch, Jax. - Solid understanding of machine learning - Experience with the infrastructure needs of large-scale model training. - Strong problem-solving skills and ability to work in a collaborative, multidisciplinary environment. Compensation We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $205,000 - $275,000 annually with a total cash compensation up to $235,000 - $325,000; however, the compensation offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience. Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end. TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.
Machine Learning Engineer, Application Software
Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Application Software Teams Our Application Software team pushes the frontier of model-based autonomous driving, improving core driving performance and developing intelligent features such as personalisation, comfort and collaboration. As a Machine Learning Engineer, you’ll lead critical initiatives to design and deliver ML-driven behaviours that scale from assisted to autonomous driving. Your work will span model architecture, data pipelines, evaluation frameworks and real-world deployment. You’ll work closely with AI Platform, Simulation, Robot Software and Model Release teams to build systems that are performant, adaptable and ready for production, while helping shape the long-term technical direction across Autonomy. 🧠 Your day-to-day - Develop and improve end-to-end driving models, advancing their performance, robustness and generalisation. - Lead technical initiatives in personalised and collaborative driving, including behaviour conditioning, comfort tuning and alignment with user preferences. - Build evaluation pipelines and metrics to assess open-loop and closed-loop driving performance and product readiness. - Curate and mine real-world and synthetic data to improve scenario diversity, coverage and feature-specific development. - Collaborate across engineering teams to integrate models, accelerate iteration and support real-world deployment. - Mentor senior engineers, drive technical alignment and influence architecture, training and deployment decisions. 🧩 What you’ll be working on - End-to-end driving intelligence: Advance the models that underpin assisted and autonomous driving, connecting model development with real-world performance. - Personalisation, comfort and collaboration: Develop ML-driven behaviours that adapt to user preferences and support comfortable, collaborative driving. - Evaluation and product readiness: Create frameworks that measure driving quality, robustness and feature performance in both open-loop and closed-loop settings. - Data-driven model improvement: Use real-world and synthetic data to uncover gaps, broaden scenario coverage and support targeted feature development. - Production-scale learning systems: Shape model architectures, training methodologies and deployment pathways, working across AI Platform, Simulation, Robot Software and Model Release. - Technical leadership: Lead cross-team initiatives and help define the long-term technical direction of our autonomy capabilities. 🙌 You should apply if - You have an extensive, proven track record of shipping deep learning systems to production. - You bring deep expertise in deep learning, particularly sequential models, control, planning or perception. - You’re proficient in Python, experienced with relevant languages such as C++ or CUDA, and confident using ML frameworks, especially PyTorch. - You have a strong foundation in software engineering practices and experience building reliable, maintainable ML systems. - You have worked with real-time systems or robotics, ideally including simulation-in-the-loop or vehicle-in-the-loop components. - You can lead technical initiatives across teams, build alignment and mentor engineers. It would also be great if you bring: - Experience in autonomous driving, imitation learning or trajectory prediction. - Familiarity with personalisation, human behaviour modelling or driver intent inference. - Experience integrating ML systems into production hardware or multi-agent simulation. 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement. More about Wayve: 🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines. Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility. How we work 💻- Locations & Flexible Working: This is a full-time role based in Sunnyvale, CA, or Detroit, MI, with a hybrid working model. Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives. 🔍 The Interview Process: Our process is clear and respectful of your time: - Initial call / recruiter screen (30 minutes) - Competency Interviews: Python programming and Pytorch debugging (2 hours) - Deep-dive technical interviews System Design, ML (1 hour) - Final interview: mission & values alignment (45 minutes) We’ll always explain the format and work around your availability. What’s in it for you (Location dependant): 💰 Salaries benchmarked against the market annually 📈 Meaningful equity, sharing in the ownership and long term success of Wayve ✈️ Relocation support and visa sponsorship where applicable ✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs 📚 Learning and development budgets with support for training, conferences and growth 🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more A quick, honest note before you apply. Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one. If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. For more information visit Careers at Wayve. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/ DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
Tech Lead Manager ML Optimization
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Waymo ML Infrastructure team accelerates Waymo’s mission, by building the best ecosystem for sustainably innovating and shipping ML powered intelligence. Research, Production, and the Hardware teams are our primary stakeholders and our work powers the development of the state of the art models in the areas of Perception and Trajectory planning that are core to our autonomous driving software. We enable our partners by offering the best in class solutions for the entire model development lifecycle. These solutions include understanding the model business goals and platform hardware characteristics, and codesign the models for the hardwares. These solutions are developed in close collaboration with teams at different modeling teams. Scale and efficiency are core tenets our infra follows. We are looking for an experienced senior TLM to join our team. In this critical role, you will lead the development and enable efficient deployment for large-scale machine learning models using state of the art advanced AI infrastructure. You will work cross functionally at the intersection of data engineering, model development, and Datacenter + on-device low-latency deployments, ensuring seamless integration across teams and technologies to power efficient innovation. You will Take ownership of improving model efficiency on different platforms and drive the model system codesign practice that meet both technical and business requirements. You will work with cutting-edge ML models that may consist of multiple billions of parameters, and apply your expertise in model optimizations and advanced algorithms toward efficient execution and deliver results on multiple hardware compute platforms. The key responsibilities for this role include: - Technical Leadership: Proactively study the SOTA model architectures and optimizations from the community and Google, for World Models, Diffusion + flow matching techniques, and translate them into measurable technical deliverables in Waymo’s onboard driving stack. - Performance Analysis: Dev tooling innovation for model performance inspector in highly distributed training/inference setups, apply roofline analysis, understand the efficiency headrooms and drive work groups to deliver the optimizations and meet the system requirements. - Strong Execution: Innovate high performance optimizations and tools for various models and large-scale training/inference including on future next-gen TPUs and low-bit precision training/inference setup, and ensure all system components align towards achieving high performance and goodput goals. - Cross-Team Leadership: Guide efforts across multiple teams and organizations to ensure seamless integration of data generation, model development, and deployment pipelines. - Mentorship & Management: Act as a mentor to junior engineers, helping to grow their technical expertise and foster a culture of collaboration and engineering excellence. Manage the IC performance for a medium size team of ~10 engineers. You Have - 10+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, training, deploying, and optimizing large-scale machine learning systems. - Experienced using ML accelerator profiling tools to uncover performance bottlenecks. - Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, JAX, or similar frameworks. - Deep understanding of state-of-the-art machine learning models and architectures such as autoregressive and diffusion transformers and familiarity with custom-kernels for diverse h/w compute based efficiency. - Strong leadership skills with experience navigating cross-functional teams and providing technical leadership projects across multiple organizations. - Excellent communication skills, both verbal and written, with the ability to translate complex technical concepts for a broad audience. - A Master’s or PhD in Computer Science, Engineering, or a related field is preferred. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $298,000 - $378,000 USD
Staff Tech Lead, Machine Learning Engineer, Percep...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the self-driving car, i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware. In this hybrid role, you'll report to a Staff Technical Lead Manager. You will: - Lead the design and development of multi-sensor, multi-task model architectures for dense and complete scene understanding with a focus on key tasks including object detection, occupancy prediction, road understanding, and trajectory planning. - Architect and develop the foundational modeling libraries and software powering model development and experimentation. - Design and implement scalable core model components, including sensor encoders, sensor fusion modules, backbones, and temporal aggregation / memory blocks. - Adapt SOTA ML technologies to unique compute requirements, leading optimizations for latency, throughput, and memory to operate efficiently within strict compute budgets. - Drive rapid prototyping by building and maintaining flexible pipelines and development environments for fast iteration on novel model designs, enabling seamless integration of field advancements and in-depth analysis of model training dynamics and learned representations. You have: - Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience - 7+ years experience in Machine Learning and/or Computer Vision - Strong expertise in Python and C++ and a solid software engineering background - Experience with ML frameworks like PyTorch, JAX, or Tensorflow We prefer: - MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline - Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI The expected base salary range for this full-time position is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $251,000 - $310,000 USD
Sr Staff Tech Lead, Machine Learning Engineer, Per...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the self-driving car, i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware. In this hybrid role, you'll report to a Senior Staff Technical Lead Manager. You will: - Set the long-term technical roadmap for next-generation multi-modal perception architectures, driving paradigm shifts in multi-task learning, spatial-temporal modeling, and scene representation. - Architect unified, scalable representations combining diverse sensor modalities across heterogeneous sensor suites. - Lead cross-functional initiatives across Perception and Planner and partner with hardware and infrastructure teams to optimize foundational architectures for onboard requirements. - Mentor ML engineers and foster an engineering culture of rapid prototyping and rigorous benchmarking. You have: - BS or MS in Computer Science, Robotics, Machine Learning, or equivalent practical experience. - 8+ years of industry experience in Machine Learning, AI or Computer Vision. - Proven track record of architecting and shipping large-scale, production-grade machine learning models. - Expert proficiency in Python, C++, and modern ML frameworks (e.g., PyTorch, JAX, TensorFlow). - Demonstrated experience leading large technical initiatives as a Tech Lead across cross-functional teams. We prefer: - PhD with a publication record at top-tier venues. - Strong industrial experience multi-modal foundation models, 3D perception, or end-to-end autonomous driving systems. - Experience designing modular, sensor-agnostic perception frameworks that scale across diverse configurations. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $298,000 - $368,000 USD
Senior Machine Learning Engineer (Infra), Driver U...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles, and have an incessant drive to improve the performance of our technology stack. You will: - Build scalable systems for training and fine-tuning large-scale models to evaluate interesting driving behaviors. - Work at the intersection of data engineering, model development, and simulation Provide guidance on architectural decisions and technical directions. Own large, complex systems, driving architectures that meet technical and business objectives. - Contribute to the production and optimization of machine learning models aiming to assess Waymo’s expansive fleet of vehicles that cumulatively travel millions of miles. - Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation, model training, and evaluation. - Collaborate cross-functionally to derive performance and system-level requirements for large ML systems. Translate product/business goals into measurable technical deliverables, ensuring system component alignment. You have: - M.S. or Ph.D. degree Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience. - 5+ years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model. - A history of contributions to machine learning tooling and frameworks e.g. PyTorch, Jax, Tensorflow, Ray, or similar. The candidate should understand both the user facing API and the internal workings. - Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks. We prefer: - 7+ years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model. - Experience in the autonomous vehicles domain, robotics, or complex simulation environments. - Familiarity with large-scale simulation platforms and their integration with ML training workflows. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000 - $263,000 USD
2027 Summer Intern, PhD, Planner Machine Learning
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you. Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship! You will: - Research, design, and implement novel deep learning architecture, multi-task loss formulations, and preference/ranking objectives in Python and Jax for Waymo’s Large Selection model. - Train and diagnose large-scale neural network using distributed TPU infrastructure, analyzing training dynamics, gradient conditioning and representation quality. - Evaluate trained models across open-loop and closed-loop benchmarks, triaging real-world driving scenarios to connect mathematical modeling choices with physical vehicle behavior. You have: - Currently pursuing a Ph.D. in Machine Learning or a related quantitative field. - Strong hands-on proficiency in Python with at least one modern deep learning framework (e.g., JAX, PyTorch). - Solid mathematical foundation in deep learning, optimization, loss formulation and empirical model diagnostics. - Experience designing, running, and analyzing rigorous ML experiments on large-scale datasets. We prefer: - Track record of first-author publications at top-tier ML, robotics, or vision venues (e.g., NeurIPS, ICML, ICLR, CoRL, ICRA, CVPR, etc). - Experience with transformer architectures, post-training/preference alignment, or sequential decision making. - Familiarity with autonomous driving and motion planning. - Experience with C++ or navigating large-scale production ML cobebases and distributed data pipelines. Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in. The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly PhD Pay $85 - $85 USD
2027 Summer Intern, MS/PhD, Software/ML Engineer,...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you. Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship! You will: - Design and build multimodal data pipelines in Python or C++ that combine vehicle sensor data (camera, LiDAR) and 3D map data for machine learning models - Prototype and iterate on Vision-Language Model (VLM) workflows to automatically detect and categorize complex real-world driving scenarios and road changes - Build ground-truth evaluation datasets, measure model precision and recall, and systematically improve detection accuracy - Integrate automated labeling pipelines into data storage and simulation testing workflows You have: - Currently pursuing a MS or PhD in a quantitative or technical field (such as Computer Science, Robotics, Machine Learning, or a related area) - Strong programming skills in Python or C++ - Experience with data analysis, SQL, and basic statistics We prefer: - Experience with computer vision, Vision-Language Models (VLMs), or prompt engineering - Familiarity with 3D geometry, coordinate transforms, or sensor data processing - Experience working with large-scale datasets or distributed data pipelines General Perks - Help solve challenging problems with a direct impact on the company - Competitive compensation packages with a housing/relocation bonus (if applicable) - Medical, dental, and vision insurance - Fun intern events and networking opportunities Onsite Perks - Free breakfast, lunch, dinner, and snacks - Free access to Google shuttles - Onsite gym Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in. The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly Masters Pay $70 - $70 USD The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly PhD Pay $85 - $85 USD
2027 Summer Intern, MS/PhD, Software Engineer, Sys...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you. The subteam for this role will be: The Model Optimization & ML Runtime team (within Smart Perception / Machine Learning) is responsible for maximizing the capability, efficiency, and hardware performance of Waymo's cutting-edge perception and foundation models. We bridge the gap between large-scale multi-task ML research (Vision Transformer backbones, 30+ perception heads, multi-sensor fusion) and real-time onboard vehicle deployment across custom automotive accelerators, developing core optimization frameworks (parameter-efficient fine-tuning, quantization, compilation, and quantization-aware training) that power the autonomous Waymo Driver. Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship! You will: - Design, implement, and benchmark parameter-efficient fine-tuning (LoRA / QLoRA) modules in JAX/Flax for multi-task Vision Transformer backbones - Develop dual-level distillation pipelines (intermediate feature matching and task-head logit distillation) to mitigate multi-task regressions during large-scale data scaling - Collaborate with model optimization, quantization, and latency teams to validate static weight folding and low-precision quantization, ensuring zero latency overhead on onboard compute platforms - Conduct extensive empirical ablations and evaluate perception metrics on large-scale autonomous driving datasets across diverse geographic domains You have: - Currently pursuing a PhD or Master's in Computer Science, Electrical Engineering, Machine Learning, Robotics, or a related technical field - Strong software engineering and deep learning development skills in Python and modern frameworks (JAX, Flax, PyTorch, or TensorFlow) - Solid theoretical understanding and hands-on experience with deep learning foundation models, Transformer architectures, and multi-task learning - Experience with model compression, parameter-efficient fine-tuning (e.g., LoRA, QLoRA, adapters), or quantization and knowledge distillation techniques We prefer: - Publication record at top-tier computer vision or machine learning conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR) - Hands-on experience with model quantization (PTQ, QAT, INT8/INT4/MX4), low-precision numerics, or hardware-aware model optimization - Experience training and scaling large vision backbones or multi-modal models on distributed accelerator clusters (TPUs / GPUs) - Familiarity with autonomous driving perception tasks (3D object detection, semantics, tracking, or pedestrian intent prediction) General Perks - Help solve challenging problems with a direct impact on the company - Competitive compensation packages with a housing/relocation bonus (if applicable) - Medical, dental, and vision insurance - Fun intern events and networking opportunities Onsite Perks - Free breakfast, lunch, dinner, and snacks - Free access to Google shuttles - Onsite gym Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in. The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly Masters Pay $70 - $70 USD The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly PhD Pay $85 - $85 USD
2027 Summer Intern, MS/PhD, Machine Learning, Driv...
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you. The subteam for this role will be: Driver Refinement foundations - The team is accountable for providing the common, consistent framework (and enabling expertise) for post-training and heuristic hill climbing across the entire Planner organization. We build fundamental platforms, including the Data Flywheel and the Reasoning platform, to assist Waymo engineers in delivering driving behavior improvements using data-driven and heuristic methods. Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship! You will: - Mine and curate dataset samples from large corpus of driving data - Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation - Optimize Multimodal generative models using RLFT. Explore Reward modeling - Design and implement Evaluation metrics and iterate on improvements You have: - Currently enrolled in a graduate program (Master's or PhD) in Computer Science or a related technical field - You have strong problem solving and programming skills in Python and/or C++ - Good understanding of Jax/Pytorch - Experience in model evaluation and developing metrics - Experience developing models We prefer: - Some understanding of SQL is preferred, not required - Previous Internship experience - PhD preferred General Perks - Competitive compensation packages with a housing/relocation bonus (if applicable) - Medical, dental, and vision insurance - Fun intern events and networking opportunities Onsite Perks - Free breakfast, lunch, dinner, and snacks - Free access to Google shuttles - Onsite gym Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in. The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly Masters Pay $70 - $70 USD The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly PhD Pay $85 - $85 USD
Forward-Deployed AI Engineer
About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Role: Forward-Deployed AI Engineer — Enterprise AI Location: Bengaluru, India Experience Level: 8+ years Work Model: Hybrid, 3 days per week in office Why Join Enterprise AI? Enterprise AI is a distinct business unit within Turing, operating with the speed, focus, and ownership of a rapidly scaling startup. When it comes to applied AI in the workplace, you’ll define the frontier by building beyond it. You’ll join the initial team of Forward-Deployed Engineers, shaping how we work while solving enterprise-grade problems for the world’s leading enterprises. As a Forward-Deployed AI Engineer, you’ll own outcomes end to end—from identifying high-value customer problems and shaping architecture to building production systems and working directly with senior client leaders. You’ll develop generative AI solutions in the real world, driving measurable impact and return on investment within large institutions. Enterprise AI is intense, intellectually challenging work. It won’t be for everyone, but it may be exactly the challenge you’re looking for. As a Forward-Deployed Engineer, You Will Find the Problem Worth Solving Work directly with customers to navigate ambiguity, uncover high-value opportunities, challenge assumptions, and translate complex business needs into clear technical direction. This requires curiosity and business acumen as you discover business workflows and jointly define the outcomes an AI solution should drive. Build Beyond the Frontier Architect and build production AI systems, from multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG) to the APIs, data pipelines, integrations, and distributed systems that make them reliable at scale. Own the Outcome You won’t simply be given a list of responsibilities—you’ll have the authority to own the outcome for your client and make a real-world impact through your work. You’ll lead solutions from discovery through deployment and measurable impact while staying hands-on and owning evaluation, observability, security, reliability, latency, scalability, and cost. The Anti-Sell High ownership and intensity: This role requires exceptional ownership and accountability. You’ll work with clients who have uncompromising expectations for quality, making this a demanding environment—and an ideal proving ground for people who seek difficult, high-impact challenges. Client-first and hybrid: This role is based in Bengaluru or Hyderabad and requires working from the office three days per week. Candidates must currently be based in one of these two cities. Relocation assistance is not available. You’ll help write the playbook: Enterprise AI operates like a startup. You may not always have an established process or playbook because you’ll be expected to apply your expertise, judgment, and technical depth to create one. Our Forward-Deployed Engineers Typically Have Deep production engineering experience: Typically 8+ years building and operating sophisticated software systems, with expertise in Python, backend systems, APIs, databases, distributed systems, system design, and cloud infrastructure. Hands-on agentic AI experience: Experience building production LLM and agent systems using orchestration, tool use, context engineering, memory and state, retrieval, and multistep workflows. Strong retrieval depth: Experience building and improving production retrieval systems, with a practical understanding of embeddings, vector and hybrid search, reranking, evaluation, and diagnosing retrieval quality. End-to-end systems ownership: A track record of taking complex systems from architecture through deployment and scale, with a practical understanding of evaluation, observability, reliability, security, guardrails, latency, scalability, and cost. Exceptional customer and technical leadership: The ability to enter unfamiliar environments, earn trust quickly, navigate ambiguity, challenge assumptions constructively, and communicate effectively with senior engineers and business executives. Client-ready communication: The ability to explain technical concepts clearly, navigate ambiguity, work with stakeholders, and remain calm under pressure. Values - We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. - We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection - We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing - Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. - Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. - Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. - Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. - Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .
Forward Deployed AI Engineer
About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Role: Forward-Deployed AI Engineer — Enterprise AI Location: New York City Experience Level: 8+ years Compensation: $200,000–$250,000 base salary + equity Work Model: In-office, typically three to five days per week, depending on client requirements Why Join Enterprise AI? Enterprise AI is a distinct business unit within Turing, operating with the speed, focus, and ownership of a rapidly scaling startup. When it comes to applied AI in the workplace, you’ll define the frontier by building beyond it. You’ll join the initial team of Forward-Deployed Engineers, shaping how we work while solving enterprise-grade problems for the world’s leading enterprises. As a Forward-Deployed AI Engineer, you’ll own outcomes end to end—from identifying high-value customer problems and shaping architecture to building production systems and working directly with senior client leaders. You’ll develop generative AI solutions in the real world, driving measurable impact and return on investment within large institutions. Enterprise AI is intense, intellectually challenging work. It won’t be for everyone, but it may be exactly the challenge you’re looking for. As a Forward-Deployed Engineer, You Will Find the Problem Worth Solving Work directly with customers to navigate ambiguity, uncover high-value opportunities, challenge assumptions, and translate complex business needs into clear technical direction. This requires curiosity and business acumen as you discover business workflows and jointly define the outcomes an AI solution should drive. Build Beyond the Frontier Architect and build production AI systems, from multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG) to the APIs, data pipelines, integrations, and distributed systems that make them reliable at scale. Own the Outcome You won’t simply be given a list of responsibilities—you’ll have the authority to own the outcome for your client and make a real-world impact through your work. You’ll lead solutions from discovery through deployment and measurable impact while staying hands-on and owning evaluation, observability, security, reliability, latency, scalability, and cost. The Anti-Sell High ownership and intensity: This role requires exceptional ownership and accountability. You’ll work with clients who have uncompromising expectations for quality, making this a demanding environment—and an ideal proving ground for people who seek difficult, high-impact challenges. Client-first and in-office: Our work is client-first, which means in-person collaboration may be required either at the client site or at our planned Manhattan office near Madison Square Park. Depending on your assignment and client needs, you should expect to work in person three to five days per week and be based in the New York City area or within a reasonable commuting distance. You’ll help write the playbook: Enterprise AI operates like a startup. You may not always have an established process or playbook because you’ll be expected to apply your expertise, judgment, and technical depth to create one. Our Forward-Deployed Engineers Typically Have Deep production engineering experience: Typically 8+ years building and operating sophisticated software systems, with expertise in Python, backend systems, APIs, databases, distributed systems, system design, and cloud infrastructure. Hands-on agentic AI experience: Experience building production LLM and agent systems using orchestration, tool use, context engineering, memory and state, retrieval, and multistep workflows. End-to-end systems ownership: A track record of taking complex systems from architecture through deployment and scale, with a practical understanding of evaluation, observability, reliability, security, guardrails, latency, scalability, and cost. Exceptional customer and technical leadership: The ability to enter unfamiliar environments, earn trust quickly, navigate ambiguity, challenge assumptions constructively, and communicate effectively with senior engineers and business executives. Client-ready communication: The ability to explain technical concepts clearly, navigate ambiguity, work with stakeholders, and remain calm under pressure. Don’t Meet Every Qualification Yet? If you don’t meet every qualification for this role, we encourage you to apply to our Forward-Deployed AI Engineer (In Training) opportunity. This role is designed for high-potential software engineers and full-stack developers who are building the production engineering, applied AI, and client-delivery skills required to become Forward-Deployed AI Engineers at Turing. Values - We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. - We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection - We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing - Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. - Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. - Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. - Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. - Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .
Site Reliability Engineer, Post Training
ABOUT THINKING MACHINES The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it. ABOUT THE ROLE We're hiring a Site Reliability Engineer (SRE) to keep our post-training and reinforcement learning (RL) systems fast, reliable, and easy for researchers to iterate on. Think of this as a production engineering or site reliability role built around model training: you'll own the health of the training runs, clusters, and pipelines that power post-training and RL at Thinking Machines. You'll work side by side with research teams during active model runs — debugging failures in real time, hardening infrastructure against the next class of problem, and building the tooling and automation that let researchers spend their time on the science instead of babysitting jobs. This role has real ownership: you'll be the person a research team calls when a run stalls at 2am, and the person who makes sure it doesn't happen again. WHAT YOU’LL DO - Own the reliability, performance, and uptime of large-scale post-training and RL training jobs, from launch through completion - Partner directly with research teams during active model runs, embedding with them to unblock training and speed up iteration - Debug failures across the full stack — accelerators, networking, storage, schedulers, and training frameworks — and drive issues to root cause - Build monitoring, alerting, and automated recovery so runs self-heal or fail fast instead of silently stalling - Improve checkpointing, fault tolerance, and job scheduling so hardware failures cost minutes, not days of compute - Build internal tools that reduce toil and improve cluster utilization across post-training and RL workloads - Participate in an on-call rotation supporting production model runs - Write postmortems and turn recurring failure patterns into permanent infrastructure fixes SKILLS & QUALIFICATIONS MINIMUM QUALIFICATIONS - 4+ years of experience as a production engineer, site reliability engineer, or infrastructure engineer operating large-scale distributed systems in production - Track record debugging complex failures across distributed systems — networking, hardware, kernel, or scheduler issues - Strong software engineering skills in Python and/or Go/C++, with the judgment to know when to script a fix versus build a system - Solid grounding in Linux systems internals and networking fundamentals - Comfortable owning production systems, including participating in on-call rotations PREFERRED QUALIFICATIONS - Experience operating GPU or TPU training clusters at scale - Familiarity with post-training and RL techniques (e.g., RLHF, PPO, DPO) and the infrastructure challenges specific to them, such as reward model serving, rollout generation, and mixed training/inference workloads - Experience with distributed training frameworks (e.g., PyTorch, Ray) and job schedulers (e.g., Slurm, Kubernetes) - Experience with high-performance networking (e.g., InfiniBand, RDMA, NCCL) and its role in distributed training performance - Experience building observability tooling purpose-built for ML training, not just general infrastructure - A track record of thriving in fast-changing, research-driven environments where priorities shift with the science LOGISTICS - Location: This role is based in San Francisco, CA. - Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $300,000- $350,000 USD. - Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together. - Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
Research, Tinker, RL Systems
ABOUT THINKING MACHINES The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it. ABOUT THE ROLE Tinker https://thinkingmachines.ai/tinker/ is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs to open access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training models with their own data, algorithms, and for their own needs. This role is all about building our training systems for Tinker, including RL systems, numerics, kernels, and beyond. WHAT YOU’LL DO In this role, you'll develop frontier customization techniques and help build the best post-training engine in the industry, drawing on a whole-stack understanding recipes, data pipelines, and training systems (numerics, kernels, and beyond). You'll engage directly with the researchers and companies pushing Tinker to its limits. This role is working with both our internal research teams as well as contributing to open science and external partners. You’ll co-design RL algorithms and training systems across the whole stack, from RL science down to numerics and kernels, to enable anyone to post-train frontier models. You’ll debug RL runs in the wild, optimize post-training pipelines, and help users reach frontier-level results, which in turn makes our platform and models the best they can be. SKILLS AND QUALIFICATIONS Required qualifications: - Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding. - Proficiency in Python and familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow, or JAX). Comfort debugging distributed training and writing code that scales. - Clarity in communication, an ability to explain complex technical concepts in writing. - Strong interest in working on Tinker and increasing usefulness and adoption. Preferred qualifications — we encourage you to apply if you meet some but not all of these: - A strong grasp of probability, statistics, and ML fundamentals. You can look at experimental data and distinguish between real effects, noise, and bugs. - Experience with RL training stability techniques for large runs. - Familiarity with low-precision training and inference: numerics, quantization, and their implications for RL. - Hands-on work with LLM serving stacks (e.g., SGLang, vLLM, TokenSpeed, or custom engines). - Experience with scaling studies for large models. - Contributions to open-source training or inference frameworks. - PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience. LOGISTICS - Location: This role is based in San Francisco, California. - Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD. - Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together. - Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed. As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
Research, Finetuning Science
ABOUT THINKING MACHINES The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it. ABOUT THE ROLE At Thinking Machines we build tools that enable people to make AI their own, customizing models to serve their unique needs. This includes the ability to train model weights. In this role, you'll work on frontier customization techniques and help build the best post-training engine in the industry – Tinker – drawing on a whole-stack understanding of RL science. Findings directly shape Tinker's training defaults, API design, and the open-source Tinker Cookbook. You'll work with our internal research teams as well as contributing to open science for external partners. WHAT YOU’LL DO In this role, you'll advance the science of fine-tuning and frontier post-training techniques. You’ll: - Contribute to areas like LoRA and parameter efficient fine-tuning and how to push customization quality, efficiency, and reliability to the frontier. - Ship research into product: inform Tinker's training defaults and primitives, and codify best-practice methods as recipes in the Tinker Cookbook. - Improve the stability, efficiency, and reliability of large-scale fine-tuning and RL runs on Tinker. - Share what you learn through papers, technical blog posts, and community contributions. You’ll contribute to areas like LoRA, parameter-efficient fine-tuning, how things interact with RL and post-training, and how to push customization quality, efficiency, and reliability to the frontier. SKILLS AND QUALIFICATIONS Required qualifications: - Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding. - Proficiency in Python and familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow, or JAX). Comfort debugging distributed training and writing code that scales. - Clarity in communication, an ability to explain complex technical concepts in writing. - Strong interest in our mission to enable custom models. Preferred qualifications — we encourage you to apply if you meet some but not all of these: - A strong grasp of probability, statistics, and ML fundamentals. You can look at experimental data and distinguish between real effects, noise, and bugs. - Prior experience with RLHF, RLAIF, preference modeling, or reward learning for large models. - Experience managing or analyzing human data collection campaigns or large-scale annotation workflows. - Research or engineering contributions in alignment, data-centric AI, or human-AI collaboration. - Experience with RL training stability techniques for large runs. - PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience. LOGISTICS - Location: This role is based in San Francisco, California. - Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD. - Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together. - Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed. As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
Conversational Modelling Research Engineer
ABOUT US Tavus https://www.tavus.io/ is a research lab pioneering human computing. We’re building AI Humans: a new interface that closes the gap between people and machines, free from the friction of today’s systems. Our real-time human simulation models let machines see, hear, respond, and even look real—enabling meaningful, face-to-face conversations. AI Humans combine the emotional intelligence of humans with the reach and reliability of machines, making them capable, trusted agents available 24/7, in every language, on our terms. Imagine a friend who can discuss any topic with you. A personal trainer that adapts to your schedule. A fleet of medical assistants that can give every patient the attention they need. With Tavus, individuals, enterprises, and developers can all build AI Humans to connect, understand, and act with empathy at scale. We’re a Series B company backed by world-class investors including Sequoia Capital, Y Combinator, and Scale Venture Partners. Be part of shaping a future where humans and machines truly understand each other. THE ROLE We’re looking for an AI Researcher to join our core AI team and push the boundaries of Foundation Multimodal Conversational Models. If you thrive in fast-moving startup environments, enjoy experimenting with new ideas, and love seeing your work come to life in production then you’ll feel right at home. YOUR MISSION 🚀 - Conduct research on Large Multimodal Models in the context of Conversational Avatars (e.g. Neural Avatars, Talking-Heads). - Develop methods to model both verbal and non-verbal aspects of conversation, adapting and controlling avatar behavior in real time, with low-latency. - Experiment with fine-tuning, adaptation, and conditioning techniques to make AudioVisual Multimodal Models, more expressive, controllable, and task-specific. - Partner with the Applied ML team to take research from prototype to production. - Stay up to date with cutting-edge advancements — and help define what comes next. YOU’LL BE GREAT AT THIS IF YOU HAVE: - A PhD (or near completion) in a relevant field, or equivalent research experience. - Hands-on experience with Large Multimodal Models and a strong foundation in generative (language) models. This could be in the context of tasks such as VQA, Audio/Video understanding tasks, captioning behavioral analysis, Translation tasks, Speech to Speech systems. - Experience in fine-tuning/adapting VLMs for control, conditioning, or downstream tasks. - Solid background in deep learning and foundation modes. - Strong PyTorch skills and comfort building deep learning pipelines. NICE-TO-HAVES - Knowledge of large-scale model training and optimization. - Experience in duplex-conversational model. - Broader understanding of generative AI across modalities. - Exposure to software development best practices. - A flexible, experimental mindset i.e. comfortable working across research and engineering. - (Bonus) Publications at EMNLP, COLING, NeurIPS, ICLR, CVPR, ICCV. Location Preferred: San Francisco (hybrid) or London. Remote within the U.S. or Europe available for exceptional candidates.
Senior Applied Research Engineer - Video
Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. ABOUT THE ROLE As an Applied Research Engineer in our Video team, you will help build the next generation of production-grade foundation models for human-centric video generation. You will join a highly focused team working at the intersection of large-scale generative modeling, distributed systems, and production engineering. Our mission is to develop and optimize video base models that power realistic, controllable, and emotionally expressive synthetic humans at scale. This is not pure research. This is applied research with direct product impact. You will work on advancing training recipes, scaling distributed systems, improving evaluation frameworks, and optimizing inference to ensure our models are high quality, stable, and efficient enough for real-world deployment. Your work will directly influence models used by tens of thousands of businesses worldwide. What you’ll do You will own and execute end-to-end research and engineering projects, from hypothesis to production impact. This includes: - Developing and scaling latent video diffusion models tailored for human-centric video generation - Designing conditioning mechanisms to improve control (pose, emotion, script, camera) without sacrificing fidelity - Advancing distributed training strategies (DDP, FSDP, DeepSpeed, sequence parallelism) under real compute constraints - Improving training stability at multi-node scale - Designing rigorous evaluation frameworks combining automated metrics and structured human evaluation - Optimizing inference for low latency, high resolution, and cost efficiency - Running controlled ablations and experiments to drive high-signal modeling decisions - Contributing to high engineering standards: reproducibility, experiment tracking, CI/CD, monitoring You will be expected to move fast, run multiple hypotheses in parallel, identify signal early, and focus on outcomes rather than exploration for its own sake. What we’re looking for MUST-HAVE - Strong experience training deep learning models at scale - Strong Python and PyTorch skills - Hands-on experience with diffusion models (image domain required; video preferred) - Experience with large scale multi-GPU / multi-node training - Good understanding of distributed training (DDP, FSDP, DeepSpeed or similar) - Ability to design controlled experiments and interpret noisy results NICE-TO-HAVE - Experience with video diffusion models - Experience in avatar or human-centric generation - Familiarity with world / interactive models - Experience with GANs or VAEs Experience optimizing inference systems for production OUR STACK - Python, PyTorch, CUDA - DeepSpeed, distributed training & inference - Sequence parallelism - AWS, SLURM, Docker - GitHub, CI/CD pipelines WHO YOU ARE - You are research-driven but outcome-focused - You care about shipping, not just publishing - You can explore multiple ideas quickly and drop low-signal directions early - You communicate clearly and present results scientifically - You operate independently but collaborate actively across teams WHY JOIN US? - Build production-scale video foundation models in a fast-growing Generative AI company - Work on human-centric video generation with real-world impact - Tackle hard problems in scaling, stability, and controllability - Influence the direction of next-generation synthetic human technology - Join a highly technical, high-ownership environment where your work ships If you want to work on cutting-edge generative video models and see your research power real-world products, we’d love to talk. Our culture At Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here. https://www.notion.so/How-we-work-at-Synthesia-f794caa72f8446efb6be22b551ce0fa2?pvs=21 SERVING 50,000+ CUSTOMERS (AND 50% OF THE FORTUNE 500) We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers https://www.synthesia.io/case-studies and what 1,200+ people say on G2 https://www.g2.com/products/synthesia/reviews#reviews. PROPRIETARY AI TECHNOLOGY Since 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind. https://www.synthesia.io/research AI SAFETY, ETHICS AND SECURITY AI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence's impact on our society is still unfolding, our position is clear: People first. Always. Learn more about our commitments to AI Ethics, Safety & Security https://www.synthesia.io/ethics.
Research Engineer, Coding Evaluation & Training Da...
ABOUT US Our mission is to raise AGI with the richness of human intelligence — curious, witty, imaginative, and full of unexpected brilliance. Surge was founded by engineers and researchers who dreamed of building the next generation AI. We're building a platform that powers the most powerful models in the world in partnership with companies like Anthropic, Google, Microsoft, and Meta. At Surge, we believe the path to AGI isn't just about scaling compute—it's about embracing the unlimited ceiling of human intelligence and creativity in the data that shapes these systems. Our platform combines elite human expertise with cutting-edge tools for scalable oversight, from building rich RL environments to conducting rigorous evaluations that go beyond benchmarks. We've run a profitable business from day one without raising venture funding. THE ROLE As a Research Engineer, Coding Evaluation & Training Data at Surge, you'll sit at the intersection of software engineering and product to build and run the systems that teach frontier models how to code. You’ll own end-to-end coding data projects for top AI labs, designing tasks, RL environments, and evaluation schemes that reflect real-world software engineering. This is an ideal role for a software engineer who wants to keep using their engineering skill set every day, but is most excited by training data quality, agentic evaluation, and system design (humans + models + tools) rather than traditional product feature work. WHAT YOU'LL DO - Own end-to-end coding data projects, from initial scoping and pilot design through execution, iteration, and scale-up. - Design agentic training workflows and task structures that mirror real-world SWE work (e.g., refactoring, debugging, code review, large-repo navigation, tool use). - Define and iterate on rubrics, golden sets, and reward signals that capture true engineering value, not just “does it compile.” - Evaluate data and worker output with strong SWE taste, and make calls about what meets the bar for frontier training. - Design and run qualification processes for coding workers, including hands-on assessments of their coding ability. - Set up or partner on complex technical environments (e.g., containers, repos, test harnesses, sandboxes, code execution infrastructure). - Partner with technical staff at our clients to translate high-level training goals into concrete projects and technical environments. - Collaborate closely with Surge engineering, product, and operations to improve our coding data products, internal tools, and execution processes. WHAT WE'RE LOOKING FOR - 3–6+ years of professional software engineering experience building and maintaining real systems. - Strong coding ability in at least one mainstream language and comfort working in production codebases. - High “taste” for good engineering: you care about correctness, code quality, and how real engineering teams actually work. - Ability to reason about and debug technical environments, including containers, dependencies, and automated test setups. - Interest in owning projects end-to-end, including scoping, workflow design, execution, and continuous improvement. - Excellent written and verbal communication skills, with the ability to speak credibly with senior client engineers and translate fuzzy goals into actionable plans. - Excitement about AI/ML systems and the role of data, evaluation, and reward design in improving agentic coding capabilities.
Forward Deployed Engineer
Forward Deployed Engineer About the Role We are seeking a Forward Deployed Engineer to help creative teams and enterprises adopt generative AI across image, video, 3D, vector graphics, and design. This role sits at the intersection of engineering, applied AI, product, and customer delivery. You will work directly with customers to understand complex workflows, identify high-value opportunities, and build solutions that connect emerging AI capabilities with real production environments. The ideal candidate combines strong software engineering skills with experience in generative AI and visual computing. You should be comfortable moving from an ambiguous customer problem to a working prototype and, ultimately, a reliable production solution. Responsibilities - Partner with creative, technical, and business stakeholders to understand their workflows, systems, and goals. - Identify opportunities to apply generative AI across image, video, 3D, vector graphics, and design. - Build prototypes, integrations, and production-ready solutions that deliver measurable customer value. - Adapt generative and multimodal models to customer-specific use cases, datasets, brand requirements, and production environments. - Integrate AI capabilities into existing creative tools, content pipelines, and enterprise systems. - Work with research, product, engineering, and design teams to translate customer needs into technical requirements and product direction. - Evaluate solutions based on quality, controllability, consistency, reliability, and production usefulness. - Diagnose technical issues across models, APIs, data pipelines, infrastructure, and customer integrations. - Document successful approaches and develop reusable implementation patterns for future deployments. - Serve as a trusted technical partner throughout discovery, prototyping, implementation, and deployment. Qualifications - Strong software engineering experience building and deploying machine learning or AI-powered applications. - Bachelor’s, Master’s, PhD, or equivalent practical experience in Computer Science, Machine Learning, Computer Graphics, Computer Vision, or a related field. - Experience with generative AI, multimodal systems, computer vision, graphics, or creative technology. - Strong programming skills in Python and experience with frameworks such as PyTorch. - Experience turning prototypes and experiments into reliable production systems. - Familiarity with APIs, cloud infrastructure, data pipelines, model serving, and enterprise integrations. - Ability to translate ambiguous customer problems into clearly scoped technical solutions. - Strong communication skills and experience working with both technical and non-technical stakeholders. - Ability to balance speed, technical quality, customer value, and scalability. - Experience in several of the following areas: - Generative image or video models - 3D generation, reconstruction, or neural rendering - Vector graphics, layout, typography, or design systems - Multimodal representation learning - Creative software and production pipelines - Model customization, fine-tuning, or inference optimization Highly Desirable - Experience in forward deployed engineering, solutions engineering, applied AI, machine learning engineering, or technical consulting. - Experience delivering complex technical implementations for enterprise customers. - Experience in professional creative domains such as VFX, games, animation, advertising, e-commerce, graphic design, or 3D production. - Experience integrating AI models into creative tools or content-production pipelines. - Experience with controllable generation, layered editing, multi-view consistency, relightable assets, structured design outputs, or brand-constrained generation. - Familiarity with model evaluation, GPU infrastructure, inference optimization, and production monitoring. - Willingness to travel periodically for customer workshops and strategic engagements. Equal Employment Opportunity We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or other legally protected statuses.
Senior/Staff FDE - Synthetic Data Generation
About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role Snorkel AI is hiring a Forward Deployed Engineer focused on Synthetic Data Generation to partner with leading AI labs and enterprises on their most critical AI initiatives. In this role, you will lead the technical execution of complex customer engagements where synthetic data is used to improve model training, evaluation, and performance. You will translate ambiguous model and data challenges into effective data strategies, build scalable generation and evaluation pipelines, and use experimentation to continuously improve data quality and downstream model outcomes. You will work across the full delivery lifecycle—from technical discovery and solution design through implementation, evaluation, and production delivery. You will also identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements. Main Responsibilities Synthetic Data Generation & Evaluation - Design and build scalable synthetic data generation, transformation, filtering, and evaluation pipelines for complex AI use cases - Translate model objectives, failure modes, and data gaps into synthetic data strategies, experiments, and technical specifications - Develop LLM- and ML-assisted workflows to generate high-quality training and evaluation datasets across targeted behaviors, domains, and edge cases - Build automated evaluators, quality checks, and measurement frameworks to assess correctness, relevance, diversity, coverage, and adherence to customer requirements - Design and run experiments to measure the impact of synthetic data on downstream model performance and iteratively improve generation approaches - Package and deliver production-grade datasets with standardized formats, quality assurance, and clear documentation Forward Deployed Engineering & Customer Partnership - Lead technical workstreams from initial solution design through production delivery, navigating ambiguity and making sound technical decisions - Build, refine, and iterate on solutions that address customer needs, incorporating feedback to ensure the delivered work provides tangible value - Rapidly prototype and productionize solutions across models, data pipelines, APIs, and custom applications - Communicate technical tradeoffs, experimental results, and recommendations clearly to technical and cross-functional stakeholders - Serve as a trusted technical partner to customers and internal delivery teams, resolving complex blockers and driving alignment Technical Leadership & Scale - Identify recurring patterns across customer engagements and turn successful solutions into reusable pipelines, evaluators, tooling, and best practices - Define and improve technical standards for synthetic data generation, experimentation, evaluation, and delivery - Partner with DaaS Engineering and Product teams to influence platform and product capabilities based on real-world customer needs - Lead technical design reviews, share expertise, and provide guidance to other engineers - Stay current with emerging synthetic data, LLM evaluation, and data curation techniques and assess their applicability to customer problems What We're Looking For - 5+ years of experience in machine learning engineering, data science, applied AI, forward deployed engineering, or a similar technical role - Strong Python skills and experience building reliable production data or ML systems, including containerizing with Docker and deploying on cloud platforms (e.g., AWS, GCP, or Azure) - Hands-on experience with LLMs—building model-based applications and data workflows with the modern GenAI/LLM stack, and integrating systems, models, and data sources through APIs - Strong understanding of ML experimentation and evaluation, including defining metrics and using empirical results to guide technical decisions - Experience building synthetic data, data augmentation, or model-generated training and evaluation datasets - Experience with LLM evaluation techniques, including LLM-as-a-judge, model-based evaluation, rubric-based evaluation, or custom evaluators - Demonstrated ability to take ambiguous technical problems from problem definition through delivery, with strong technical communication and experience working directly with customers and cross-functional stakeholders - Experience serving as a technical lead—setting technical direction, driving architecture and key decisions, mentoring engineers, and creating reusable approaches that influence broader engineering or product outcomes Preferred Qualifications - Experience developing datasets for fine-tuning, preference optimization, or benchmarking, including human-in-the-loop generation and review workflows - Experience building agentic environments and tasks—repo-scale coding tasks, tool-agent-user interaction design, and agent tool protocols and interoperability - Experience with reinforcement learning for LLMs, including reward and verifier design and RL with verifiable rewards (RLVR) - Experience working in fast-paced, customer-facing environments where requirements and technical approaches evolve quickly Compensation The base salary range for this position is $180,000–$320,000 , with an additional variable compensation opportunity. The exact mix of base salary and variable compensation will depend on the role level and work location. Final compensation will be determined based on job-related skills, experience, relevant education or training, interview performance, and other business considerations. Most offers include equity and benefits. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role $180,000 - $320,000 USD Be Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Senior / Staff AI Engineer
About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About The Team Snorkel's AI Platform organization builds the infrastructure and systems that power AI development at scale - synthetic data generation, evaluation, agentic workflows, simulation environments, LLM infrastructure, and distributed compute. Our platform enables engineering and research teams to rapidly experiment with models and agents, measure their behavior, and turn successful experiments into reliable production systems. We're a small team operating at the intersection of distributed systems and applied AI, and we're in the middle of a foundational shift toward agent-first workflows where models interact with tools, environments, data, and other agents over long-running trajectories. The systems we build need to make these inherently non-deterministic workloads observable, reproducible, measurable, and scalable. You will help define how we do that. About The Role We're looking for AI Engineers who combine strong software and distributed systems fundamentals with experience operating AI systems in production. You'll build the infrastructure that lets teams create, experiment with, evaluate, and operate LLM and agentic workloads at significant scale - from synthetic data and evaluation pipelines to simulation environments, orchestration systems, and LLM infrastructure. You'll work on systems where correctness is not defined by a single deterministic output. Instead, you'll build the infrastructure needed to understand behavior across models, prompts, tools, environments, and multi-step trajectories, and to continuously improve those systems through experimentation and evaluation. We are looking to grow our team of AI Engineers, and are hiring at multiple levels. What You'll Do - Design and build infrastructure for running large-scale agentic workloads, including multi-step agents interacting with tools, external services, sandboxes, and simulated environments - Build scalable synthetic data generation and automated labeling systems that allow teams to create, refine, and evaluate high-quality training and evaluation datasets - Design evaluation infrastructure for measuring AI system behavior across models, prompts, tools, environments, and multi-step trajectories - including reproducible experiments, benchmark execution, regression detection, and continuous evaluation - Build orchestration and distributed compute systems for running thousands to millions of AI experiments and simulations reliably across heterogeneous compute environments - Develop infrastructure for agent simulation environments, including environment provisioning, isolation, lifecycle management, and scalable execution - Build and operate LLM infrastructure for routing, rate limiting, retries, caching, provider failover, cost attribution, and efficient execution across multiple model providers - Instrument agent and model workloads so failures are observable and debuggable - capturing traces, model interactions, tool calls, environment state, evaluation results, latency, reliability, and cost - Design systems that make non-deterministic workloads reproducible and measurable, allowing engineers to compare experiments, diagnose behavioral regressions, and understand why an agent succeeded or failed - Improve the developer experience for AI experimentation by building APIs, SDKs, workflow abstractions, and tooling that make it easy to move workloads from local development to large-scale production execution - Collaborate with research, product, and engineering teams to turn experimental AI workflows into reliable, reusable platform capabilities What You'll Bring - 5+ years building production software systems, with experience in AI/ML infrastructure, ML platforms, distributed systems, data platforms, or backend infrastructure - Experience operating non-deterministic AI or ML workloads in production or at significant scale — you are comfortable reasoning about behavior across models, tools, environments, and multi-step execution - Experience building infrastructure for experimentation, evaluation, model development, synthetic data, agentic workflows, training, inference, or production ML systems - Strong proficiency in Python and experience building production-quality APIs, services, and developer tooling - Strong background in distributed systems and cloud platforms (AWS preferred), including compute orchestration, storage, networking, isolation, and failure handling - Experience with workflow or distributed execution frameworks such as Prefect, Airflow, Dagster, Ray, Kubernetes, or similar systems - Strong understanding of production system fundamentals - observability, telemetry, reliability, performance, debugging, incident response, and cost management - Ability to reason about AI system quality beyond traditional service metrics, including evaluation design, experiment reproducibility, behavioral regressions, and model or agent variability - Track record of leading complex engineering initiatives, influencing stakeholders, and delivering measurable impact - Ability to work in a fast-paced environment with strong technical communication skills - Fluency with modern AI and developer tooling and a willingness to rapidly evaluate and adopt new models, frameworks, infrastructure, and techniques as the ecosystem evolves Nice to Have - Experience building or operating LLM or agent infrastructure, including model gateways, agent runtimes, tool execution, tracing, or multi-agent systems - Experience building evaluation or experimentation platforms for LLMs, agents, or other probabilistic systems - Experience with synthetic data generation, automated labeling, data refinement, or dataset quality systems - Experience building reinforcement learning environments, agent simulations, benchmarks, or other environment-based evaluation systems - Experience running large-scale distributed AI workloads across containers, Kubernetes, serverless compute, sandboxes, or heterogeneous compute environments - Experience with LLM observability, tracing, prompt/version management, token and cost attribution, rate limiting, caching, or multi-provider routing - Experience designing isolation and sandboxing infrastructure for executing model-generated code or tool calls safely - Experience building shared AI platform libraries or SDKs consumed by multiple teams, including versioning, backwards compatibility, and migration support - Experience in hyper-growth startup environments or scaling engineering organizations - Prior experience as a Tech Lead, Team Lead, or hands-on Engineering Manager Why This Role You'll have meaningful ownership over the infrastructure that determines how quickly Snorkel can experiment with, evaluate, and productionize new AI systems. This isn't a role focused on training a single model or maintaining traditional ML pipelines - you'll build the platform that makes large-scale AI experimentation possible. You'll work on some of the hardest emerging infrastructure problems in AI: operating non-deterministic systems reliably, reproducing agent behavior across environments, evaluating long-running trajectories, scaling simulations and experiments, and turning rapidly evolving research workflows into robust production systems. The architecture decisions made by this team will define how Snorkel builds and operates AI systems for years to come. Snorkel is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role - Be Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. Be Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Research Scientist - Frontier Benchmarks
About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! ABOUT THE ROLE We're looking for a Research Scientist to lead the design of next-generation benchmarks and datasets that push the boundaries of frontier model evaluation. You'll define what "good" looks like across a range of hard tasks, drawing on conversations with customers and academic partners to ground your datasets in real performance gaps. You'll build both the benchmarks that measure those gaps and the training data that helps close them, then partner with delivery, product, and go-to-market to bring what you build into production. This role is ideal for someone who wants to shape how the field measures progress in frontier AI, and who's energized by doing that work inside a fast-moving, cross-functional startup. MAIN RESPONSIBILITIES - Design state of the art datasets that drive frontier model training and evaluation based on current model performance and academic partnerships - Translate benchmark insights into clear, compelling narratives that articulate the ROI of expert-curated data for customer-facing presentations, technical reports, and go-to-market materials. - Work cross-functionally with data operations, product, engineering, and strategy to surface research findings that inform the company roadmap. - Stay at the frontier of LLM evaluation research and bring best practices into Snorkel's workflows - Represent Snorkel's research externally through publications, blog posts, conference talks, and customer engagements that advance the conversation around data-centric AI PREFERRED QUALIFICATIONS - Strong research background in AI/ML evaluation, NLP, or related fields, with a track record of rigorous experimental design — especially around measuring the impact of training and evaluation data on model behavior. - Exceptional communication skills — able to present complex technical findings clearly to both technical and non-technical audiences - Comfort operating in a fast-moving, cross-functional environment with ambiguous problem spaces - Genuine interest in GTM strategy, startup dynamics, and the commercial side of AI data services. - Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role $200,000 - $375,000 USD Be Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Research Scientist
About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! As a Research Scientist at Snorkel AI, you will bridge the gap between cutting-edge research and real-world AI systems. This is a hands-on role where you will prototype, build, and deploy innovative AI solutions—translating research breakthroughs into scalable, practical applications that solve real-world problems. Snorkel AI operates in a fast-paced, high-impact environment, where we move quickly to push the boundaries of what’s possible. We’re looking for someone who thrives on rapid iteration, solving open-ended challenges, and driving innovation from research into production. Location: San Francisco OR REMOTE Main Responsibilities - Design, implement, and validate novel AI techniques for data development such as synthetic data generation, utilizing techniques such as LLM as a Judge - Prototype and build end-to-end workflows, integrating research ideas into scalable systems. - Write high-quality, maintainable code, ensuring robust implementation of research-driven innovations. - Move fast and adapt—iterating on solutions in response to new challenges, customer needs, and emerging research. - Work closely with real-world design partners, testing solutions in applied settings with measurable impact. - Collaborate with research scientists, engineers, and industry partners to push forward Snorkel AI’s broader research initiatives and rapidly productionize prototypes. Preferred Qualifications - Strong expertise in AI, NLP, multi-modal models, LLMs, and generative AI, with an emphasis on applied research and system-building. - Experience in developing, experimenting, and deploying AI models at scale. - Proficiency in Python and machine learning frameworks (NumPy, Scikit-learn, Pandas, PyTorch, TensorFlow, etc.). - Experience with software engineering best practices (e.g., clean coding, modular design, version control). - Familiarity with ML infrastructure, cloud platforms (AWS, Google Cloud), and accelerators (GPUs, TPUs). - Ability to work in a fast-moving, iterative environment, comfortable with ambiguity and open-ended challenges. - A bias for action—willing to roll up your sleeves, experiment, and move quickly to solve problems. This role is ideal for candidates who love both research and building real AI systems in a dynamic, high-impact setting. A Ph.D. in machine learning or a related field with a strong publication record is preferred, but we also welcome applications from those with equivalent expertise gained through industry experience, research labs, or other career paths. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role $200,000 - $375,000 USD Be Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Director, Research - Evaluation & Training
About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! ABOUT THE ROLE We're looking for a manager to lead a team of researchers to focus on data evaluation, error analysis and data valuation methods to predict model performance. This team is responsible for showcasing the value and quality of Snorkel’s data for model training and evaluation, understanding where today's frontier models fall short, and turning that understanding into a point of view on what benchmarks and datasets these models will benefit from. You and your team will be responsible for Snorkel’s data design flywheel by analyzing model failures, finding capability and skill gaps in current models, suggesting the next benchmarks to invest in and then proving the value of this data for our customers. MAIN RESPONSIBILITIES - Own a multi-quarter roadmap centered on novel evaluation, error analysis, and data valuation techniques - Synthesize and share trends from model-failure analysis and benchmarking into recommendations on the datasets the community should focus on and the ones Snorkel should invest in — making this team a primary input to the company's data strategy. - Focus on data valuation techniques that quantify how Snorkel data meaningfully improves model performance - Lead and grow a team of researchers, setting a high bar for quality, rigor and speed of execution - Act as the primary bridge between the team's findings and Product, GTM, and our customers PREFERRED QUALIFICATIONS - 7+ years in applied AI, ML, or research roles, with 4+ years managing technical teams. - A leader who has repeatedly turned research and analysis into business outcomes, and who instinctively connects technical findings to market and customer needs. - Strong business and market judgment in the AI/ML space — you understand the competitive and frontier-lab landscape and can prioritize accordingly. - Technically conversant and credible: enough depth in LLM evaluation, benchmarking, and model behavior analysis to set direction, judge experimental quality, and pressure-test results — without needing to be the deepest technical expert in the room. - A nose for trends: able to look across many evaluation results and failure cases and extract the signal that should drive what gets built next. - Excellent communication and storytelling skills, with the ability to make technical results legible and persuasive to non-research audiences. - Familiarity with data valuation or data attribution research is a strong plus. - Bonus: experience working with frontier labs, public benchmarks, or commercial AI data/eval products. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role $275,000 - $425,000 USD Be Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Software Engineer, Agent (Spanish speaking)
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in London, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences. Professional fluency in both Spanish and English. EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent (New Grad 2027)
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent (Italian speaking)
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in London, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent (German speaking)
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in London, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences. Professional fluency in both German and English. EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent (French speaking)
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in London, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences. Professional fluency in both French and English. EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent (Dutch speaking)
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in London, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent (Cantonese Speaking)
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences - Proficiency in Cantonese is required to support interactions with Cantonese-speaking clients. EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent (Brazilian Portuguese spe...
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Language fluency - professional fluency in both Brazilian Portuguese and English - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent (Arabic speaking)
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in London, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent - Travel & Hospitality
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. ABOUT THE TRAVEL, TRANSPORTATION AND HOSPITALITY TEAM - The Travel, Transportation and Hospitality (TTH) supports some of the largest airlines, hotel chains, rental car brands, cruise lines and travel tech companies in the world. Our customers are frontiers in the travel space, and are true thought partners in shaping our platform, helping reinvent what hospitality looks like in this new era. Our customers rely on us to not only deliver standout customer experiences, driving stronger growth in their business. - Our TTH team is constantly pushing the bounds of what is possible within this industry and beyond. We help support our customers in the moments that matter — whether that’s proactively encouraging new bookings to prepare for exciting events, or helping guests rebook their flights or stays during times of distress. We help our customers maximize the lifetime value of their guests and build products to delight guests at every touchpoint. - We’re a small and scrappy team, and we support each other with any deliverables we have to meet. Every engineer on TTH is also a product-led thinker; every PM on TTH is tinkering and developing tangible prototypes; and every strategist on TTH is capable of owning an agent end to end. As a part of this team, you’ll set the standard on what it means to go beyond your role, and help build the travel industry of the future. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Building innovative multimodal experiences: Spearhead cross-cutting initiatives, partnering with the voice and Experience SDK teams to bring to life embedded voice mode in mobile apps. This brand new product allows users to talk, tap and text with our agents all in a single view — unlocking communication through rich visualizations, and accuracy in input collection with chat, with the ease and efficiency of voice. - Shipping complex booking experiences: Build personalized booking flows, including leveraging Google Maps APIs to support searching for properties via an embedded map view, developing a recommendation engine based on past reservations and orchestrating seamless payment collection to complete the full booking lifecycle. - Abstracting complex systems into packages: Modernize legacy reservations systems by creating Sierra packages that optimize querying and updating trips for customers across the board. You’ll be challenged to think deeply about how to orchestrate each step of these workflows to maximize efficiency while upholding reliability and accuracy. - Improving the capabilities of our built in integrations: Expand platform extensibility by introducing new capabilities to our existing integrations. An example is extending our MCP integrations to support MCP UI, which allows customers to dynamically host their custom UI resources on our embedded chat windows. WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems. - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments. - A builder and tinkerer's mindset with high agency - you find creative ways to overcome obstacles and ship. - Comfort working directly with customers to understand their needs and solve real-world problems. - Excellent communication skills—clear, direct, and persuasive across technical and non-technical audiences. - Excitement in the travel space and a genuine care for helping improve the guest experience as a whole. Our customers care deeply about their guests, and we carry that through what we build every day. EVEN BETTER... - Language Fluency: Professional fluency in both Spanish and English. - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent - Insurance
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. ABOUT THE FINANCIAL SERVICES TEAM - Our financial services customers span insurers that provide protection for life’s most challenging moments, systemically important banks, neobanks committed to building more delightful banking software, vertically integrated ecosystems like Rocket Companies, and more. The decisions we make impact millions of end customers and billions of dollars in economic activity. - Our Financial Services team partners closely with these organizations to set their AI strategies and build modern tools that carefully handle moments when a person’s private anxiety meets an institution’s procedural muscle—the hours after a family discovers their home has been damaged by a wildfire and begins filing a claim; the difficult conversation following the loss of a loved one as beneficiaries navigate a life insurance claim; the frustration of dropping a phone, shattering the screen, and trying to quickly understand coverage and arrange for a repair or replacement. - Sierra’s Financial Services team is transforming the customer experience and building technology that makes the industry more accessible, human, and affordable for everyone. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large insurance companies that consistently outperform human agents in filing claims quickly and consistently. - Develop and refine AI agents capable of navigating complex customer interactions, like generating a quote for insuring a modified 1960s Corvette. - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems. - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments. - A builder and tinkerer's mindset with high agency - you find creative ways to overcome obstacles and ship. - Comfort working directly with customers to understand their needs and solve real-world problems. - Excellent communication skills—clear, direct, and persuasive across technical and non-technical audiences. - Genuine interest in Financial Services and improving the end customer experience. Experience in insurance technology, implementations at financial institutions, working inside of these institutions or familiarity with financial services security and compliance requirements (coverage advice, PII handling, etc.) are a strong plus. EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent - Financial Services
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. ABOUT THE FINANCIAL SERVICES TEAM - Our financial services customers span systemically important banks, neobanks committed to building more delightful banking software (1 in 3 of the world's leading banks use Sierra!), insurers that provide protection for life’s most challenging moments, vertically integrated ecosystems like Rocket Companies, and more. The decisions we make impact millions of end customers and billions of dollars in economic activity. - Our financial services team partners closely with these organizations to set their AI strategies and build modern tools that carefully handle moments when a person’s private anxiety meets an institution’s procedural muscle - the instant before a family learns whether they are pre-approved for a mortgage; the claustrophobic half hour after someone notices a fraudulent charge; the frustrating experience of losing a card and needing to order a new one. - Sierra’s Financial Services team is transforming the customer experience and building technology that makes the industry more accessible, human, and affordable for everyone. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems. - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments. - A builder and tinkerer's mindset with high agency - you find creative ways to overcome obstacles and ship. - Comfort working directly with customers to understand their needs and solve real-world problems. - Excellent communication skills—clear, direct, and persuasive across technical and non-technical audiences. - Genuine interest in Financial Services and improving the end customer experience. Experience in financial technology, implementations at financial institutions, working inside of these institutions or familiarity with financial services security and compliance requirements (fair lending, PII handling, etc.) are a strong plus. EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Software Engineer, Agent
ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in London, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Staff Software Engineer, Perception (R5421)
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities. In this role, you'll lead the technical development of advanced machine learning solutions that define the future of perception for autonomous systems. You'll own the team's most challenging technical problems, drive architecture and model development across multiple efforts, and influence how foundation models are adapted, evaluated, and deployed for real-world autonomy. Working closely with researchers, perception engineers, autonomy engineers, and platform teams, you'll bridge cutting-edge AI research with scalable production systems while mentoring engineers and raising the technical bar across the organization. What You'll Do: Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems. Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks. Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks. Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments. Research-to-Production – Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability. Cross-functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems. Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements. Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery. Required Qualifications: Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience. Expertise of machine learning fundamentals. Experience training an deploying ML models for computer vision in a production setting. Strong understanding of 3D vision problems/algorithms. Experience with machine learning frameworks such as PyTorch and TensorFlow. Demonstrated expertise in deploying models using TensorRT and ONNX. Proficiency in C++ and Python. Strong analytical and problem-solving skills, with the ability to translate research into practical applications. Ability to obtain a SECRET clearance Preferred Qualifications: Experience with developing autonomous systems for defense customers. Experience with training/finetuning vision-language models, vision-language-action models, and/or world models. Contributions to open-source projects in machine learning or computer vision. Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).
Staff Deep Learning Engineer, State Estimation (R5...
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: Join Shield AI’s Hivemind SDK State Estimation & Vision team to build deep learning capabilities that help autonomous systems understand their motion and localize in the world when GPS is unavailable or unreliable. You will work at the intersection of deep learning, 3D computer vision, and geometric estimation, developing learned components for vision-based navigation. You will own the model development pipeline—from selecting tools, defining annotation needs, and cleaning data through training, evaluation, integration support, and deployment recommendations. Hands-on experience with Deep Learning and 3D computer vision and geometry is required; prior experience specifically in vision-based navigation is optional. What you'll do: Develop and evaluate models for tasks such as feature detection and matching, visual correspondence, depth estimation, relative pose estimation, and image-to-map localization. Combine learned visual representations with geometric methods to improve localization accuracy, robustness, and recovery under challenging conditions. Own data preparation and supervision strategies, including dataset curation, annotation requirements, labeling tools, automated quality checks, and coverage analysis. Select and integrate deep learning tools and build reproducible training workflows, including experiment tracking, configuration management, and dataset and model versioning. Design evaluations that measure both model performance and downstream localization outcomes across changes in lighting, viewpoint, altitude, terrain, weather, and sensor characteristics. Analyze failures and use controlled experiments to prioritize improvements to data, supervision, models, and integration. Partner with state estimation engineers to integrate learned measurements and confidence estimates into VIO and terrain-relative navigation systems. Profile models against onboard compute, memory, and latency constraints, and work with deployment engineers on optimization and runtime validation. Deliver tested, documented components and interfaces for Hivemind SDK, collaborating with software, systems, and flight test teams. Required qualifications: M.S. in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or a related field; minimum 4+ years of related professional work experience with an M.S. degree, or 2+ years with a Ph.D. Hands-on experience designing, training, debugging, and evaluating models using PyTorch or an equivalent framework, including architecture selection, loss design, optimization, and augmentation that preserves geometric consistency. Strong foundations in camera models, coordinate transformations, projective geometry, and multi-view geometry, with practical experience in one or more fields: vision-based navigation, visual geolocation, Structure from Motion (SfM), SLAM, 3D reconstruction, depth estimation or similar fields. Expertise in every area is not required. Strong Python skills and experience writing maintainable, reusable software. Demonstrated ability to take a computer vision capability from problem definition and raw data through training, evaluation, and integration readiness. Experience building pipelines for sensor data ingestion, cleaning, filtering, deduplication, and dataset versioning. Ability to select and integrate development tools and build reproducible training workflows, including configuration management, experiment tracking, checkpointing, and GPU performance troubleshooting. Experience designing benchmarks, preventing data leakage across related sequences or locations, analyzing performance across operating conditions, and connecting model metrics to downstream geometric or localization accuracy. Ability to profile inference latency and memory use, document model interfaces and preprocessing, assess accuracy–compute tradeoffs, and advise deployment engineers on export, precision, and runtime optimization. Ability to communicate assumptions, experimental findings, and design tradeoffs clearly and translate research into working software. Preferred qualifications: Experience with aerial imagery, geospatial data, elevation maps, or matching observations across viewpoint, lighting, season, or sensor modality Experience with model export, quantization, TensorRT, ONNX, or deployment on embedded compute platforms. Experience validating perception or robotics systems on physical platforms. Relevant publications, open-source contributions, or demonstrated delivery of production computer vision systems, familiar with methods including: feature correlation, correlation or cost volumes, and matching methods for correspondence, stereo, optical flow, or localization. learning priors over scene geometry, depth, motion, or appearance to improve estimation under sparse, ambiguous, or degraded observations. applying diffusion models or flow matching to computer vision, geometric inference, or conditional generation. Experience in aerospace and / or defense industry. You do not need every nice-to-have to succeed in this role. We welcome engineers with strong Deep Learning and 3D vision foundations who are excited to develop expertise in state estimation and navigation to apply.
Senior Staff Software Engineer, Perception (R4985)
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities. In this role, you'll develop and deploy advanced machine learning models that enable autonomous systems to better understand, reason about, and interact with their environment. You'll partner closely with machine learning researchers, autonomy engineers, perception engineers, and platform teams to translate emerging AI capabilities into reliable, production-ready systems for U.S. and international defense customers. This is an ideal opportunity for engineers who enjoy building state-of-the-art AI systems while solving the practical challenges of deploying them on operational autonomous platforms. What You'll Do: Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems. Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks. Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks. Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments. Research-to-Production – Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability. Cross-functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems. Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements. Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery. Required Qualifications: Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience. Mastery of machine learning fundamentals. Experience training an deploying ML models for computer vision in a production setting. Strong understanding of 3D vision problems/algorithms. Experience with machine learning frameworks such as PyTorch and TensorFlow. Demonstrated expertise in deploying models using TensorRT and ONNX. Proficiency in C++ and Python. Strong analytical and problem-solving skills, with the ability to translate research into practical applications. Ability to obtain a SECRET clearance Preferred Qualifications: Experience with developing autonomous systems for defense customers. Experience with training/finetuning vision-language models, vision-language-action models, and/or world models. Contributions to open-source projects in machine learning or computer vision. Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).
Senior Software Engineer, Perception (R5420)
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities. In this role, you'll develop and deploy advanced machine learning models that solve real-world perception challenges for autonomous systems. You'll own major features from model development through deployment, working closely with machine learning researchers, perception engineers, autonomy engineers, and platform teams to bring cutting-edge AI capabilities into production. This is an ideal opportunity for engineers who enjoy solving difficult perception problems while building reliable, production-ready ML systems that operate on autonomous platforms in complex operational environments. What You'll Do: Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems. Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks. Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks. Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments. Research-to-Production – Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability. Cross-functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems. Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements. Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery. Required Qualifications: Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 4 years and a Master’s degree; or 2 years with a PhD; or equivalent work experience. Prioficiency of machine learning fundamentals. Experience training an deploying ML models for computer vision in a production setting. Strong understanding of 3D vision problems/algorithms. Experience with machine learning frameworks such as PyTorch and TensorFlow. Demonstrated expertise in deploying models using TensorRT and ONNX. Proficiency in C++ and Python. Strong analytical and problem-solving skills, with the ability to translate research into practical applications. Ability to obtain a SECRET clearance Preferred Qualifications: Experience with developing autonomous systems for defense customers. Experience with training/finetuning vision-language models, vision-language-action models, and/or world models. Contributions to open-source projects in machine learning or computer vision. Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).
Generative AI Application Engineer, Learning & Dev...
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: The Senior AI Engineer, Hivemind Learning & Development is a hands-on individual contributor who will build the AI-powered products, content systems, and measurement capabilities that help engineers learn Hivemind faster and apply it successfully. Embedded within the Hivemind Learning & Development team, this role combines production AI engineering, developer experience, and technical education. You will own an AI training coach that provides grounded, context-aware guidance; create tooling that turns learning objectives and product changes into high-quality workshops; and partner with autonomy experts to produce deeply technical curricula, labs, and assessments. The role works closely with Applications Engineering, Hivemind engineering and Customer Success. Success is defined by trusted learning products that ship, shorter time to technical proficiency, faster and more consistent workshop development, content that stays current with Hivemind releases, and clear evidence that training improves customer capability and product adoption. What you'll do: Develop an AI-powered training coach that helps people learn Hivemind concepts, products, and development workflows. Create highly technical Hivemind training materials and hands-on workshops for engineers and other technical learners. Build prompt-based tooling that generates workshops and supporting learning content from defined objectives, audiences, and source materials. Create LLM-based tooling that automates the ongoing upgrade and improvement of Hivemind training and educational materials. Build AI tools and systems that enable, streamline, and automate Hivemind Learning & Development workflows. Required qualifications: Progressive experience building production software, AI-enabled products, developer tools, technical learning platforms, or comparable systems. Hands-on experience integrating large language models, generative AI APIs, retrieval-augmented generation, agents, prompt workflows, or AI-assisted automation into production or enterprise environments. Strong software engineering fundamentals, including API design, testing, observability, documentation, secure coding, maintainable architecture, and operational ownership. Professional proficiency in Python and the ability to read, debug, and create credible examples in modern C++. Experience translating complex software or systems concepts into clear technical documentation, hands-on labs, workshops, developer education, or enablement material. Ability to learn a sophisticated technical product quickly, work directly with subject-matter experts, and convert ambiguous needs into practical, testable learning solutions. Experience evaluating AI system quality using automated tests, structured human review, telemetry, or task-based performance measures. Clear written and verbal communication skills, sound technical judgment, and a collaborative style suited to engineers, instructors, customers, and cross-functional partners. Preferred qualifications: Experience with autonomy, robotics, aerospace, defense, simulation, distributed systems, or safety-critical software. Experience with developer education, instructional design, learning science, intelligent tutoring systems, or assessment design for highly technical audiences. Familiarity with AI evaluation and observability, prompt and agent testing, vector databases, enterprise search, model gateways, and deployment in restricted or disconnected environments. Experience designing and facilitating hands-on technical workshops for customer engineers, including troubleshooting live technical environments. Bachelor's degree in Computer Science, Engineering, Robotics, Data Science, Learning Technology, or a related field, or equivalent practical experience. Why this role matters: Hivemind gives engineers a comprehensive platform to develop, test, and deploy AI pilots. The value of that platform depends on how quickly technical teams can build sound mental models, complete real workflows, and apply the software with confidence. This engineer will create the learning systems that make expert knowledge available at the moment of need, reduce the delay between product change and customer readiness, and help the Learning & Development team scale quality without losing technical rigor.
ML Model Serving Engineer
About Sesame Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human. With this vision, we're designing a new kind of computer, focused on making voice agents part of our daily lives. Our team brings together founders from Oculus and Ubiquity6, alongside proven leaders from Meta, Google, and Apple, with deep expertise spanning hardware and software. Join us in shaping a future where computers truly come alive. RESPONSIBILITIES: - Turbocharge our serving layer, consisting of a variety of LLM, speech, and vision models. - Partner with ML infrastructure and training engineers to build a fast, cost-effective, accurate, and reliable serving layer to power a new consumer product category. - Modify and extend LLM serving frameworks like VLLM and SGLang to take advantage of the latest techniques in high-performance model serving. - Work with the training team to identify opportunities to produce faster models without sacrificing quality. - Use techniques like in-flight batching, caching, and custom kernels to speed up inference. - Find ways to reduce model initialization times without sacrificing quality. REQUIRED QUALIFICATIONS: - Expert in some differentiable array computing framework, preferably PyTorch. - Expert in optimizing machine learning models for serving reliably at high throughput, with low latency. - Significant systems programming experience; ex. Experience working on high-performance server systems—you’d be just as comfortable with the internals of VLLM as you would with a complex PyTorch codebase. - Significant performance engineering experience; ex. Bottleneck analysis in high-scale server systems or profiling low-level systems code. - Always up to date on the latest techniques for model serving optimization. PREFERRED QUALIFICATIONS: - Familiarity with high-performance LLM serving; ex. experience with VLLM, SGlang deployment, and internals. - Experience with a public cloud platform such as GCP, AWS, or Azure. - Experience deploying and scaling inference workloads in the cloud using Kubernetes, Ray, etc. - You like to ship and have a track record of leading complex multi-month projects without assistance. - You’re excited to learn new things and work in a multitude of roles. Sesame is committed to a workplace where everyone feels valued, respected, and empowered. We welcome all qualified applicants, embracing diversity in race, gender, identity, orientation, ability, and more. We provide reasonable accommodations for applicants with disabilities. Contact careers@sesame.com for assistance. Full-time Employee Benefits: - 401 (k) max employer match: 3.5% of compensation - 100% employer-paid health, vision, and dental benefits for you and your dependents - Unlimited PTO and sick time - Flexible spending account with employer matching up to $1,650/year (medical FSA) - Guardian Employee Assistance Program (EAP) - Opportunity to share in the company's success with competitive stock options Benefits do not apply to contingent/contract workers.
Data Engineer, Machine Learning
About Sesame Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human. With this vision, we're designing a new kind of computer, focused on making voice agents part of our daily lives. Our team brings together founders from Oculus and Ubiquity6, alongside proven leaders from Meta, Google, and Apple, with deep expertise spanning hardware and software. Join us in shaping a future where computers truly come alive. ABOUT THE ROLE We're looking for a Data Engineer to build and maintain the data pipelines that feed Sesame's AI models. You'll collaborate directly with machine learning engineers and researchers — your job is to make sure they have the right data, in the right shape, at the right time to train, evaluate, and ship models. Sesame's data is rich and complex: conversations, voice, sensor signals, and product telemetry. You'll design the systems that take raw, unstructured, multimodal data and turn it into clean, versioned, well-documented datasets that ML teams can trust and build on confidently. This is a deeply technical, infrastructure-focused role — closer to ML engineering than traditional data analytics. You'll be deeply embedded with ML teams, understanding their workflows and building infrastructure that accelerates the full model development lifecycle — from data collection and labeling through training and evaluation. RESPONSIBILITIES: - Design and build production data pipelines that prepare conversational, voice, and multimodal data for model training and evaluation. - Partner directly with ML engineers to understand data requirements for new models and experiments, and deliver datasets that meet those needs. - Build and maintain infrastructure for dataset versioning, lineage tracking, and reproducibility — so any training run can be traced back to its exact data. - Develop data quality frameworks that catch issues before they become model quality issues: schema validation, drift detection, and coverage monitoring. - Optimise large-scale data processing for cost and performance across Sesame's cloud infrastructure. - Build tooling that makes it easy for ML engineers and researchers to discover, explore, and request data independently. - Define and enforce data governance and privacy standards, particularly around sensitive conversational and voice data. - Contribute to architecture decisions around Sesame's broader data platform as the team and data volume grow. REQUIRED QUALIFICATIONS: - 5+ years in data engineering, with meaningful experience supporting ML or AI teams specifically. - Strong SQL and Python skills — you'll use both daily. - Experience building and operating ETL/ELT pipelines at scale using modern data platforms and tooling. - Experience with workflow orchestration systems such as Airflow, Dagster, or Prefect. - Hands-on experience with ML data workflows: training data pipelines, dataset versioning, data labeling pipelines, or model evaluation data. - A solid understanding of how ML teams work — you don't need to train models; what matters is understanding what makes a good training dataset and why data quality directly affects model performance. - Comfort working with unstructured and semi-structured data — audio, text, JSON logs — not just clean relational tables. - Strong communication skills. You'll be embedded with ML engineers and need to bridge data systems and model requirements effectively. PREFERRED QUALIFICATIONS: - Vector databases, embedding storage, or feature stores. - Data from hardware or embedded systems: telemetry, sensors, real-time streams. - Distributed compute frameworks for large-scale data processing such as Ray or Spark. - Kubernetes and managed Kubernetes environments such as GKE or EKS. - Data privacy frameworks, especially around voice or conversational data. - Building internal tooling or self-serve data platforms. Sesame is committed to a workplace where everyone feels valued, respected, and empowered. We welcome all qualified applicants, embracing diversity in race, gender, identity, orientation, ability, and more. We provide reasonable accommodations for applicants with disabilities. Contact careers@sesame.com for assistance. Full-time Employee Benefits: - 401 (k) max employer match: 3.5% of compensation - 100% employer-paid health, vision, and dental benefits for you and your dependents - Unlimited PTO and sick time - Flexible spending account with employer matching up to $1,650/year (medical FSA) - Guardian Employee Assistance Program (EAP) - Opportunity to share in the company's success with competitive stock options Benefits do not apply to contingent/contract workers.
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