Data Client Onboarding Specialist in San Francisco

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role OpenAI Robotics depends on high-quality real-world robot data from a large, live operational environment. That environment has many deployed workcells, changing configurations, and little tolerance for downtime. We are seeking a Field Engineer to help keep that environment running well. You will own the day-to-day technical health of robotic workcells used in ongoing data acquisition operations, diagnose and resolve failures across hardware and software, and build the practical tools, documentation, and support workflows that make operators and technicians more effective. The work is close to the floor, close to the failure modes, and close to the research impact. This role sits at the intersection of software, robotics hardware, and live operations. The best people in it are practical, technically sharp, calm under pressure, and motivated by making real systems work reliably at scale. This role will be based in San Francisco, CA 5 days per week and offer relocation assistance to new employees. In this role, you will: Serve as an engineering owner for keeping a fleet of robotic workcells online in daily operation. Diagnose, fix, mitigate, or escalate issues spanning mechanics, electronics, controls, software interfaces, logs, and configuration. Partner closely with technicians, operators, and engineering teams to improve scalable fleet support processes. Build or spec lightweight hardware and software tools that improve monitoring, diagnostics, recovery, and handoffs. Create documentation, SOPs, and diagnostic playbooks that turn en

About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety. About the Role Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research? This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused. Our relevant publications: Preparedness framework Preparing for future AI capabilities in biology Safety evaluations hub OpenAI GPT5 System Card Evaluating Fairness in ChatGPT Improving Model Safety Behavior with Rule-Based Rewards OpenAI Model Spec Your Responsibilities: Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios. Develop structured taxonomi

About The Team Our mission is to bring OpenAI products to life for every customer. Demo Experience equips customer-facing teams with the experiences, systems, and confidence to make frontier capabilities tangible, relevant, and trustworthy. OpenAI’s products and customer needs are evolving rapidly. Demo Experience closes the gap between a frontier capability and a credible customer experience—making new capabilities understandable, demonstrable, and reusable quickly at scale. Working across Product, Engineering, Marketing, Operations, and GTM, we turn recurring customer needs into reusable capabilities and raise the standard for every customer conversation. About The Role Demo Experience Engineers work at the intersection of product engineering, technical storytelling, and GTM execution. You will own ambiguous, high-leverage problems end to end—from building agentic prototypes to creating the infrastructure and self-service tools that make them reliable and reusable. Your work will help customer-facing teams move faster, reduce avoidable failures, and translate frontier product capabilities into clear customer value. You will also turn recurring patterns from customer-facing work into product feedback, launch-readiness improvements, and scalable systems. Success in this role means teams can demonstrate new capabilities sooner and with greater confidence. Recurring requests become reusable capabilities instead of one-off work. Demo experiences are accurate, reliable, and safe. Insights from customer-facing work improve product and readiness decisions. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In This Role, You Will Own end-to-end demo readiness for new and priority product capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths. Build compelling prototypes, LLM agents, and reference flows that mak

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with

About the Team: Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams. Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage. About the Role We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may not be the strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you. Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, t

About the team OpenAI’s Education team is building products and experiences that help learners, educators, and institutions benefit from AI in ways that are rigorous, useful, and grounded in real learning outcomes. The work spans both consumer and B2B education, with close collaboration across engineering, learning science, design, data, and research. This team sits in a highly strategic investment area for OpenAI, with strong opportunities to shape how product ideas flow across consumer and institution-facing experiences. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the role We’re looking for a product-minded Full Stack Engineer to help build OpenAI’s education products from the ground up. You’ll own end-to-end development across the stack, from early concepting and prototyping through production launch and iteration. This is an opportunity to work on a highly strategic, early-stage product area where engineering judgment, product sense, and customer empathy all matter. You’ll partner closely with leaders across the education org, including learning scientists, researchers, designers, and cross-functional partners, to turn emerging ideas into durable product experiences for schools, universities, and other education stakeholders. In this role, you will: Build and ship product experiences across the full stack for OpenAI’s education offerings Own projects end-to-end, from ideation and technical design through implementation, launch, and iteration Work closely with learning scientists and researchers to translate learning goals and evidence into product decisions Collaborate with design, data, and cross-functional partners to build thoughtful, high-quality user experiences Help define the engineering foundation for a growing education pod, including patterns, systems, and technical

About the Team OpenAI's Industrial Compute organization is responsible for planning, delivering, operating, and optimizing the compute infrastructure that powers frontier AI. As OpenAI scales toward becoming an intelligence utility, Industrial Compute coordinates a complex lifecycle spanning infrastructure strategy, capacity planning, provider partnerships, fleet operations, product demand, and financial planning. The organization manages one of the largest and fastest-growing compute footprints in the world, where decisions around capacity allocation, deployment readiness, utilization, reliability, and product demand directly impact product availability, customer experience, and business performance. The Capacity Systems team builds the software platforms, data systems, and automation frameworks that connect these functions into a shared operating model. We transform fragmented planning workflows into scalable systems that enable teams to understand what compute was contracted, delivered, healthy, allocated, and ultimately converted into business and research outcomes. About the Role We are seeking a Capacity Systems Software Engineer to build the platforms and services that power Industrial Compute planning, forecasting, optimization, and operational decision-making. In this role, you will design and develop software systems that connect infrastructure delivery, fleet health, capacity allocation, demand forecasting, deployment readiness, financial planning, and product consumption into a unified system of record. Your work will help OpenAI make better decisions about where compute should be deployed, how capacity should be allocated, and how infrastructure investments translate into business value. You will partner closely with Capacity Planning, Fleet Operations, Infrastructure Engineering, Product, Finance, Supply Chain, and Strategic Sourcing teams to replace spreadsheet-driven workflows with scalable software systems that enable visibility, automation, and dec

About the Team The Premium team owns some of the highest-leverage customer-facing levers in ChatGPT’s consumer revenue business, spanning the paid customer journey: helping users understand the value of paid plans, convert with confidence, and continue finding lasting value in their subscription. Our work is highly cross-functional, partnering with Product, Data Science, Design, FinEng, Finance, Legal, Support, and Marketing to improve free-to-paid conversion, renewal, customer lifetime value, and revenue while keeping the experience trustworthy, scalable, and low-friction. In This Role, You Will: Lead and scale an engineering team responsible for some of ChatGPT’s most important subscription and monetization experiences. Own the technical execution for Premium customer experiences across plan merchandising, paywalls, upgrade flows, checkout UX, plan management, renewals, downgrades, and cancellation. Partner with Product and Data Science to run high-quality experiments across upgrade, trial, renewal, downgrade, and cancellation flows. Improve key subscription metrics including conversion, renewal, churn, ARPU, and lifetime value. Build reliable customer-facing Premium experiences for purchase, plan management, renewal, downgrade, cancellation, and access-related states at scale. Partner closely with FinEng and other platform teams to evolve the billing, payments, and entitlement capabilities that power Premium experiences. Collaborate closely with Product, Design, Data Science, Finance, Legal, Support, and Marketing on monetization strategy and execution. You Might Thrive in This Role If You: Have 5+ years of engineering management experience, Have strong technical expertise in backend, frontend, or full-stack development, with experience building growth-oriented features. Have a track record of improving conversion, retention, or monetization through experimentation and data-driven product engineering. Are experienced with subscription products, plan merchandising

About the Team The Integrity team builds the systems OpenAI uses to understand, prevent, and respond to misuse across our products. We partner with Product, Policy, Safety Systems, User Operations, Security, Legal, Privacy, OpenAI for Government, and research teams to turn policy and threat models into product controls, review workflows, measurement systems, and enforcement paths. About the Role We are hiring a Product Manager to own Integrity's product strategy for sensitive deployments: contexts where model capability, customer or deployment setting, privacy constraints, and misuse potential make the operating bar unusually high. This includes government and other high stakes deployments, regulated or high-trust enterprise contexts, zero data retention and privacy-constrained environments, and agentic workflows where harm can unfold across many steps rather than a single prompt. The Sensitive Deployments PM will focus on high-consequence use cases relevant to government deployments and broader deployment-readiness questions for high-risk domains (e.g., healthcare), while building reusable Integrity capabilities for agentic detection and enforcements in these environments. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Own the roadmap for sensitive deployment Integrity controls and readiness criteria. Define how we measure residual risk, decision quality, review quality, and mitigation effectiveness. Build agentic investigation and context-assembly workflows for complex, multi-step misuse patterns. Partner with Policy, Legal, Privacy, Safety Systems, User Ops, Government, and product teams to build shared capabilities. Create launch and deployment playbooks for sensitive customer, capability, and product contexts. You might thrive in this role if you: Have shipped complex product systems in AI, integrity, trust and safety, security, privacy, risk, government, regulated enterprise, or AI safety. Can turn am

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a Rack Power Engineer with deep expertise in high-power conversion and distribution to design, qualify, and support power systems for AI supercomputers. You will own rack power solutions—including power shelves, AC/DC rectifiers, power supply units (PSUs), power management controllers (PMCs), and high-current distribution—from requirements and supplier development through deployment. You will also monitor fleet rack power health, lead debugging and root-cause investigations, and drive improvements into hardware, firmware, and qualification coverage. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own rack power architecture and requirements for high-power AI supercomputing systems, including power budgets, AC input interfaces, DC distribution, redundancy, efficiency, serviceability, and integration with data center infrastructure. Drive the design and supplier development of power shelves, rectifiers, PSUs, PMCs, busbars, connectors, and protection circuits. Review electrical designs and control behavior, and evaluate performance, cost, reliability, and availability trade-offs. Define and execute component, shelf, and rack qualification plans covering load transients, current sharing, hot-swap, startup and shutdown, redundancy failover, fault protection and recovery, thermal limits, and AC disturbances and ride-through

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Programmatic Ads team integrates with external demand partners (DSPs, SSPs, etc) through OpenRTB. We drive performance optimization (latency, conversion, engagement, fill rate, etc) for our programmatic ad products. We are also responsible for building internal tools to better enable cross-functional teams. What you’ll do: Lead one or two partner integrations, and work closely with product managers, data scientists, other cross-functional teams, and external partners to understand business requirements and translate them into technical solutions. Use AI to accelerate team execution, system design, and decision-making, applying sound judgment to validate outputs and ensure correctness and quality. Independently drive the full software development lifecycle, including ideation, technical design, prototyping, development, and release. Ind

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a Corporate Accounting Manager to support the general ledger, the close, and our accounting processes and controls as Baseten scales. This is a hands-on, individual-contributor role for someone who wants full ownership of the core accounting function at a company where the entity structure, transaction volume, and reporting requirements are growing quickly. You’ll join the corporate accounting team and take on the general ledger, vendor contract review, the close calendar, and our internal control environment as the business grows. We are focused on tightening close procedures, strengthening controls, and building reporting rigor to support the scale ahead. You’ll partner closely with FP&A, Data, and cross-functional partners to make sure the books close on time and accurately every cycle. Baseten is building the infrastructure layer for AI-native companies, and we're scaling quickly - in headcount, entity structure, transaction volume, and contract complexity and volume and vendor size. If you want real ownership over a growing function on a lean team, this role offers real scope. RESPONSIBILITIES General Ledger and Financial Reporting Own day-to-day execution of general ledger journal entries, account reconciliations, and monthly financial statement preparation as the entity structure grows Own recurring close areas, including accruals, prepaids, fixed assets, and equity compensation Lead

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We are bringing our people systems in-house on Workday, and we are hiring our first dedicated Workday Analyst to make it excellent. You will join while the implementation is underway, ramp alongside our deployment partner, and own the tenant from go-live onward. This is a hands-on configuration role: you will build business processes, manage security, load data, and test releases yourself, and you will teach others on the People team to do the same as we grow. If you want to shape a Workday environment from its first day in production instead of inheriting years of someone else's decisions, this is that rare opening. RESPONSIBILITIES Own day-to-day Workday configuration: business processes, security groups and roles, custom reports, calculated fields, and tenant settings Build and run EIB loads for data changes, mass updates, and audits Own the twice-yearly Workday release cycle: evaluate new features, regression-test, and roll out changes safely Shadow the implementation build, then take over tenant ownership at go-live Monitor integrations and triage issues with our IT team and vendors Support payroll configuration in partnership with our Accounting team and payroll services provider Field and resolve system requests from employees, managers, and the People team Mentor teammates so Workday administration becomes a team capability, not a single point of failure REQUIREMENTS 4+ years administering a live Workday

About the Team OpenAI Finance helps ensure the organization is set up for success in pursuit of its mission of ensuring that artificial general intelligence benefits all of humanity. Within Finance, the Revenue Accounting, Technical team partners with Product, Strategic Partnerships, Business Development, Growth, Legal, Deal Desk, GTM, Strategic Finance, Revenue Accounting, and Finance Systems to enable scalable, operationally sound monetization. We advise on commercial and contract design, establish clear accounting positions under ASC 606, and translate those conclusions into repeatable processes, systems, controls, and reporting. About the Role We’re looking for a Manager of Revenue Accounting, Technical to drive the end-to-end technical revenue and operational workstream for OpenAI’s strategic commercial deals—from early structuring and deal-desk review through contracting, launch, and ongoing governance. Reporting to the Head of Revenue Accounting, Technical, you will serve as a key revenue advisor for complex and non-standard strategic deals, translating commercial objectives into revenue models that are economically sound, accounting-compliant, and operationally executable. You will partner with senior team members on the most novel or high-risk matters across strategic collaborations, cloud marketplaces, platform and distribution deals, licensing and revenue-share models, joint go-to-market initiatives, research collaborations, and other emerging commercial structures. You will engage from the earliest stages of a deal to shape economics, pricing, commercial terms, contract language, and product design; define the supporting data, billing, settlement, reporting, systems, controls, and revenue-recognition model; and drive cross-functional readiness through launch. After launch, you will help govern amendments, monitor whether the model is operating as intended, resolve execution issues, and evolve the approach as the partnership or business model changes. Thi

We’re looking for a strategic operator to help advance OpenAI’s life sciences capabilities and translate them into meaningful scientific and commercial impact. Working closely with research teams and external partners, you’ll identify opportunities to improve AI models, products, and supporting infrastructure, and lead partnerships and strategic initiatives that bring these capabilities into real scientific workflows. This role combines partnership development, strategic judgment, and hands-on execution. You’ll help determine where OpenAI can make the greatest contribution, identify the expertise and resources needed, and bring together the right partners to move from an idea to demonstrated impact. In this role, you will: Shape capability priorities. Work with research and cross-functional teams to identify and prioritize new life sciences capabilities, balancing scientific value, technical feasibility, and commercial potential. Build and execute partnerships. Develop data, research, and commercial partnerships with biotechnology companies, pharmaceutical organizations, and other participants in the life sciences ecosystem. Translate capabilities into real-world applications. Partner with external organizations to apply OpenAI’s technology in scientific workflows, evaluate its usefulness, and use those learnings to inform further development. Structure effective collaborations. Work with legal, finance, research, and other teams to define partnership scope, align incentives, and navigate data access, intellectual property, commercial terms, and governance. Lead strategic initiatives. Identify and own projects that advance scientific capabilities and create long-term value for OpenAI, including licensing, joint development, and new applications of AI. Drive operational execution. Establish clear objectives, milestones, and ownership; coordinate resources; and resolve obstacles across internal teams and external partners. Expand access to expertise. Identify gaps in