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About the Team OpenAI’s Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company’s most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. We are hiring Data Scientists across several teams that contribute to safety in different ways, including: Safety Systems Integrity Product Policy This is a high-impact role operating at the intersection of product, safety, policy, and research. About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: Measure harmful or abusive behavior across OpenAI’s products Detect fraud, manipulation, coordinated misuse Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows Design experiments and causal analyses to understand product, policy, and mitigation impacts Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs Translate ambiguous safety risks into measurable problems and evidence-based recommendations Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes Build zero-to-one analytical systems in rapidly evolving domains Ideal Candidate We’re looking for strong Data Scientists who thrive in ambiguous, high-leverage environments. You may be a fit if you have: Strong statistical reasoning and analytical judgment Experience with experimentation, causal inference, or obse

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in NYC. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or compar

About the Team OpenAI’s Finance and Revenue Operations organization builds the commercial infrastructure that enables the business to scale with speed, discipline, and financial integrity. Deal Desk operates as the commercial strategy and governance function at the intersection of Sales, Partnerships, Legal, Technical Revenue, Finance, Order Management, Billing Operations, Product, and GTM Systems. We architect complex enterprise transactions, turn ambiguity into executable decisions, and create the guardrails that let the business move quickly with operational and financial discipline. As OpenAI’s enterprise business grows in scale and complexity, Deal Desk defines how novel commercial motions become durable operating capabilities. We convert precedent-setting deal decisions into repeatable policy, controls, workflows, and systems requirements. About the Role We are hiring a Strategic Deals & Commercial Architecture Lead to lead the structuring and governance of OpenAI’s most complex enterprise transactions. This is a senior individual-contributor leadership role for someone with exceptional enterprise deal judgment, operational rigor, and a builder mindset. You will serve as the commercial architect for high-stakes opportunities, translating ambiguous requirements into coherent deal structures, approval strategies, and executable quote-to-cash plans. Your work will shape more than individual transactions. You will establish decision principles and precedent, clarify tradeoffs, and turn recurring patterns into scalable guidance, controls, systems requirements, and enablement. You will own the commercial decision and governance layer that helps strategic opportunities move decisively while managing downstream risk across contracting, billing, revenue recognition, provisioning, reporting, controls, auditability, and customer experience. The right candidate can move seamlessly between advising on a single high-value transaction and improving the operating model be

About the Team Our 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 We are seeking a Senior Actuator Design and Integration Engineer to lead the development of custom electromechanical actuators for advanced robotic systems. You will own actuator development from early architecture and concept generation through prototype validation and system integration, partnering closely with mechanical, electrical, controls, firmware, reliability, and manufacturing teams. This role focuses on the design, integration, and validation of precision electromechanical systems, including motors, transmissions, sensing, structural components, and thermal architectures. You will help drive actuator development across the full engineering lifecycle while establishing scalable design, test, and integration practices for future robotic platforms. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Lead the architecture, design, and integration of custom robotic actuators, including motors, transmissions, sensing, thermal systems, structural components, and packaging. Define actuator requirements and system-level trade studies around torque density, bandwidth, efficiency, thermal performance, backdrivability, inertia, reliability, manufacturability, and cost. Design precision electromechanical assemblies with strong attention to tolerances, alignment, load paths, thermal expansion, sealing, wear, and serviceability. Drive actuator integration into robotic systems, partnering closely with controls, firmware, electrical, and robotics software teams to optimize closed-loop pe

About the Team The Core Services team is responsible for building and managing foundational services. It acts as the bridge between core infrastructure (e.g. compute, storage, networking) and product engineering teams, and enables product teams to move fast, build reliably, and scale efficiently. About the Role As a software engineer in the core services team, you will design and operate critical backend platforms such as caching systems, workflow orchestration, metadata stores, and file services. You’ll focus on building highly reliable, scalable, and performant systems that serve as the backbone of our products. We’re looking for people who are passionate about building infrastructure that empowers product teams, love working on distributed systems challenges, and enjoy creating well-designed APIs and abstractions that accelerate development. 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: Design, build, and maintain shared infrastructure services such as caching layers, workflow orchestration (Temporal), metadata stores, and file storage services. Collaborate with product teams to provide scalable, reliable primitives that abstract the complexities of distributed systems. Improve performance, resilience, and scalability of core services that power customer-facing applications. You might thrive in this role if you: Have experience with distributed systems, caching infrastructure (e.g., Redis, Memcached), metadata storage (e.g., FoundationDB), or workflow orchestration (e.g., Temporal, Cadence). Have experience running containerized services in cloud environments and integrating them into automated build/test/release (CI/CD) workflows. Understand trade-offs in consistency models, replication strategies, and performance optimization in multi-region systems. Excel at communication and collaboration with cross-functional teams, and are obsesse

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Tokyo. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Travel is expected in this role, mainly within Japan. To succeed in this position you must be bilingual—fluent in both Japanese and English (spoken and written). Please note that your resume must be submitted in English, and the interview process will include conversations in both languages. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bri

About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod

About the Team The Software Engineering team is responsible for designing and building the scalable, performant, and secure backend systems that power our products—from early prototypes to large-scale deployments. We collaborate closely with product, hardware, and full-stack teams to ensure our infrastructure enables fast iteration while setting a strong foundation for long-term growth. About the Role As a Backend Engineer , you will design and build services, APIs, and infrastructure that support evolving product needs. You’ll apply a deep understanding of backend systems and maintain enough end-to-end context—from hardware to cloud—to guide technical decisions that best serve the product and team. We’re looking for engineers who thrive in fast-paced, collaborative environments and care deeply about building robust systems that scale. This role is based in San Francisco, CA . We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Architect, build, and maintain high-performance, secure backend systems. Design APIs, data models, and infrastructure to support evolving product needs. Balance near-term development velocity with long-term maintainability and scalability. Collaborate with cross-functional teams to ensure cohesive, end-to-end solutions. You might thrive in this role if you: Have 7+ years of professional software engineering experience, with a focus on backend systems. Have a proven track record of building and scaling systems from early stage to large scale. Are proficient with Python and Go, and familiar with a range of server-side technologies. Have a strong grasp of system design, performance optimization, and security best practices. Can reason about full-stack tradeoffs from hardware through cloud infrastructure. (Nice to have) Have experience with distributed systems and cloud architectures. (Nice to have) Bring a background in instrumentation, analytics, and performanc

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or co

About the team The Pricing & Monetization team is responsible for how OpenAI products create and capture value. We partner closely with GTM, Finance, and Product to design pricing models, packaging, and commercial strategies that support adoption, growth, and long-term scaling of the business. To thrive in this team, you need to be a proactive problem-solver who excels at bringing structure to ambiguous challenges. Our work demands strategic thinking, cross-functional collaboration, and precision in execution. Team members succeed when they are analytical, detail-oriented, skilled at balancing multiple priorities, and passionate about driving high-stakes projects forward to deliver meaningful results. About the role We are looking for a Pricing Strategist to shape the pricing frameworks, commercial policies, and decision principles that govern our most consequential commercial decisions. This role works closely with senior leaders across GTM and Finance to define our overall pricing strategy for our sales managed segment as well as the key pricing guardrails and commercial pricing framework we enable to help our sellers and customers move fast and land mutually beneficial commercial agreements at scale. The ideal candidate is comfortable developing durable monetization frameworks and commercial policies, analyzing tradeoffs, and supporting high-impact decisions. They bring structure to ambiguity, communicate tradeoffs crisply, and know when an exception reveals a one-off need versus a broader opportunity to improve our commercial model. This role will report to the Head of Go-to-Market Pricing. In this role, you will Develop frameworks and strategies that guide commercial pricing decisions. Design commercial constructs—including commitments, incentives, and risk-sharing approaches—that address customer needs while supporting healthy unit economics and long-term growth. Build and evolve discounting frameworks, guardrails, and approval principles that improve pric

Location: San Francisco, CA (Hybrid: 4 days onsite/week). Relocation assistance available. About the Team: We build foundational platform software that enables reliable, secure, and performant products. The team works across system layers and partners closely with adjacent engineering groups to deliver robust capabilities from concept through launch. About the Role: We’re seeking a System Software Engineer to design, implement, and debug core platform components and the pipelines that build and update system images. You’ll work across operating system layers, focusing on performance, security, and deep system debugging to ship production‑grade systems. In this role, you will: Design, implement, and debug system‑level components and services across kernel and user space. Configure and maintain OS platform services (init, services, networking, security policies) and related tooling. Build and operate image and update pipelines, ensuring reliability, reproducibility, and rollback safety. Instrument and analyze performance using profiling and tracing; optimize CPU, memory, I/O, and power usage. Own platform observability and reliability: logging, crash capture, watchdogs, and diagnostics. Collaborate with cross‑functional teams to define interfaces and deliver end‑to‑end features. Establish strong engineering practices: code review, CI, reproducible builds, and release management. Partner with external suppliers to support builds and deployments. You might thrive in this role if you: Have shipped production systems software on modern operating systems. Are proficient in C/C++ and a scripting language, and comfortable with OS internals (concurrency, memory management, filesystems, networking, power management). Bring strong systems debugging skills using debuggers, tracers, profilers, and logs across kernel/user‑space boundaries. Understand configuration of platform services and interfaces, and can translate requirements into stable, well‑documented APIs. Are fluent in u

About the Team The Pricing & Monetization team is responsible for how our products create and capture value. We partner closely with Product, GTM, and Finance to design pricing models, packaging, and commercial strategies that support adoption, growth, and long-term scaling of the business. To thrive on this team, you need to be a proactive problem-solver who excels at bringing structure to ambiguous challenges. Our work demands strategic thinking, cross-functional collaboration, and precision in execution. Team members succeed when they are analytical, detail-oriented, skilled at balancing multiple priorities, and passionate about driving high-stakes projects forward to deliver meaningful results. About the Role We are looking for a Pricing Strategist with hands-on consumer pricing experience to shape how we price, package, and monetize our products across our consumer offerings. You’ll work closely with senior leaders across Product, GTM, and Finance to define pricing approaches, improve commercial decision-making, and bring more rigor to how we monetize our offerings. You should be comfortable building monetization frameworks and commercial policies, analyzing tradeoffs, supporting and driving high-impact decision-making. You should also care deeply about the customer perspective and believe that strong pricing reflects a real understanding of customer value, needs, and friction points in order to build pricing that is clear, fair, and aligned with how customers experience our products. This role will report to the Head of Product Pricing for Chat & Codex. What you’ll do Develop pricing and packaging strategy across subscription tiers, usage limits and entitlements, credits and overages, and emerging monetization models, balancing customer value, growth, and unit economics. Develop innovative commercial constructs to better serve our customers. Partner with Product, GTM, and Finance leaders to ensure pricing aligns with product value, the roadmap, commerc

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for engineers to build the infrastructure that powers Codex agents in production. This role focuses on the systems that let models safely execute code, interact with tools, complete long-running tasks, and operate reliably and efficiently at scale. You’ll design and operate the infrastructure behind sandboxed execution, orchestration, stateful workflows, app-server and SDK boundaries, and model rollouts. You’ll work at the intersection of distributed systems, developer tooling, and AI, building primitives that make Codex faster, safer, more reliable, and easier for the rest of the organization to build on. What You’ll Do Design and build execution environments for AI agents, including sandboxing, isolation, and reproducibility. Develop systems for agent orchestration across multi-step, tool-using workflows. Build infrastructure for running, testing, and debugging code generated by models. Create state and memory systems that allow agents to persist context across long-running tasks. Optimize tokens, latency, reliability, and cost across Codex’s production fleet. Support model rollouts, capacity planning, and the core tradeoffs between quality, speed, and economics to manage a fleet of frontier agents at scale. Build shared platform capabilities that unblock product teams, partner teams, and open source Codex. Yo

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Sydney. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production. Build full-stack systems that deliver customer value and sharpen how we learn. Embed closely with customer teams, understand their needs, and guide adoption of what you build. Scope work, sequence delivery, and remove blockers early. Make trade-offs between scope, speed, and quality; adjust plans to protect delivery. Contribute directly in the code when progress or clarity depends on it. Codify working patterns into tools, playbooks, or building blocks that others can use. Share field feedback that helps Research and Product understand where the models succeed and where they can improve. Keep teams moving through clarity and follow-through. You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work. Have scoped and delivered complex systems in fast-moving or ambiguous environments. Write and review production-grade code across frontend and backend using Python, JavaScr