Research Intern in San Francisco

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 applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users. What You’ll Do Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows. Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases. Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation. Analyze failures in production and systematically improve robustness and reliability. Build feedback loops and data systems that get better real-task data into evaluation and research. Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on. Help define what “good” looks like for agents completing complex tasks end-to-end. You Might Be a Good Fit If You Ha

About the Team The Product Policy team develops and implements policies that shape how OpenAI’s technology is built and used. We work with teams across the company to turn complex questions about AI’s benefits and risks into practical guidance for responsible research, product development, and deployment. About the Role As Product Policy Manager, Regulation, you will map external regulatory and legislative trends and synthesize them into concrete research, product, and policy requirements. You will connect deep expertise in regulation and public policy with a sophisticated understanding of AI and strong product judgment. Your remit will span frontier AI, youth, wellbeing, use in high-stakes domains, deceptive use, and other emerging issues. Working closely with Legal and Global Affairs, you will help Product, Engineering, Research, and Safety teams understand what external developments mean for their work, what decisions or evidence are needed, and how to act. We’re looking for someone who combines deep regulatory and public-policy expertise with an in-depth understanding of AI and a demonstrated ability to advise product and engineering teams. You should be able to move from complex external developments to clear decisions and requirements that teams can implement. This role can be based in San Francisco or remote. 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: Map and prioritize regulatory and legislative developments across jurisdictions and AI issue areas. Distinguish enacted requirements, proposals, guidance, and emerging expectations; assess their relevance, uncertainty, timing, and implications for our models and products. Translate external developments into actionable research questions, evaluation needs, product requirements, and policy recommendations. Identify gaps in evidence, define the intended outcome and acceptance criteria, and make tradeoffs and open questions c

About the Team The Plugin Ecosystem team builds the platform and product experiences that let people extend ChatGPT and Codex. We work on plugins, skills, connectors, interactive apps, and open standards like the Model Context Protocol (MCP). We make plugins easy to discover, install, and use, ensure they’re invoked at the right time, and help people find new ways to get value from them. We want anyone to be able to turn a useful workflow into a plugin, share it, and have other people use it. A plugin can package instructions and skills with connections to the tools and data it needs. Our work spans creation and publishing, reliable execution across our products, clear permissions and approvals, and the controls admins need to bring plugins to their organizations. We work closely with research to improve plugin quality as models evolve. About the Role We’re looking for product-minded engineers to build the systems behind plugins and improve how models use them. Depending on your focus, you may scale generalist infrastructure and identity-related integrations across products, or improve plugin quality at the intersection of backend engineering and applied AI or work on the product experience itself to drive plugin usage. You’ll work across teams and own problems from diagnosis and design through implementation and release. This role is based in San Francisco. 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 and ship APIs, SDKs, and services that developers use to extend ChatGPT and Codex. Build intuitive experiences that help users discover, install, and use plugins to get more done. Make plugins easier to create, test, publish, update, and share. Improve when and how models use plugins, from choosing the right plugin to completing a task. Work with Research to diagnose failures and measure improvements as models evolve. Improve plugin reliability and interaction quality acros

About the Team Compute Foundations builds the software that manages OpenAI’s GPU compute infrastructure across sites, data centers, and infrastructure providers, supporting model training and inference. Our systems turn large, heterogeneous fleets of machines into dependable compute for research and products. We build Kubernetes-based control planes, controllers, services, and APIs that coordinate the lifecycle of machines and clusters. We connect global infrastructure management with the realities of bare-metal systems, giving clients consistent interfaces across differences in hardware, topology, and provider behavior. About the Role You will build distributed systems that provision, configure, and manage compute throughout its lifecycle. Your work will connect global services and Kubernetes controllers with the systems that bring machines online, update them safely, and recover them when something goes wrong. This role combines software architecture with an understanding of how machines and data centers work. You might design a lifecycle API, improve controller performance under high concurrency and provider rate limits, or trace a provisioning failure from an API through reconciliation to network boot or host configuration. You will help these systems remain reliable as the fleet expands across sites and generations of GPU hardware. We value depth in relevant systems and the ability to connect layers. You do not need to arrive as an expert in every component of the stack. In this role, you will: Design, build, and operate Kubernetes-based controllers and distributed services that coordinate infrastructure across sites, isolate failures, and scale as GPU capacity grows. Define APIs and resource models that let clients request and track lifecycle operations through consistent interfaces across hardware platforms and providers. Build provisioning and configuration services that coordinate network boot, hardware management interfaces, and the deployment of firmware,

About the Team OpenAI’s Healthcare team is working to ensure that advances in AI meaningfully improve health for everyone. We build AI systems that support patients, clinicians, and healthcare organizations while setting a high standard for deploying AI responsibly in a high-stakes domain. On the Healthcare team, we are building products and infrastructure that bring OpenAI’s capabilities into healthcare organizations and clinical workflows. We serve health care systems, insurance companies, and the broad range of healthcare IT companies. Our products include connecting ChatGPT with healthcare data and systems and building reliable enterprise experiences that can operate within complex security, privacy, compliance, and interoperability requirements. We work closely with product, research, design, security, privacy, GTM, and our healthcare customers to turn powerful AI capabilities into dependable products that clinicians and healthcare organizations use in their everyday work. About the Role We are looking for backend and full-stack software engineers to build the systems behind OpenAI’s healthcare products. You will work across backend services, APIs, data systems, integrations, and product surfaces to connect AI with healthcare workflows and enterprise data. You’ll tackle the technical challenges involved in making these systems secure, reliable, observable, and scalable enough for real-world healthcare environments. This is a product-engineering role for someone who can move between customer problems and complex system architecture, and who is comfortable owning ambiguous problems end-to-end. In this role, you will: Design and build backend and full-stack systems powering OpenAI’s healthcare products. Build services, APIs, and data pipelines that connect OpenAI products with healthcare systems and enterprise data. Develop integrations with electronic health records and other healthcare data sources. Design systems that meet demanding requirements around privacy,

About the Team Enterprise Marketing helps the world’s largest organizations understand, adopt, and scale AI. We create programs that bring OpenAI’s products, research, and perspective closer to the priorities, decisions, and work of enterprise customers. Some of the most consequential opportunities cannot be served by adapting an existing campaign, event, or playbook. They require a new model: a way for customers to experience what is possible, learn by doing, and turn insight into action. Our team builds and scales those models across markets. About the Role We are looking for a senior program builder to create differentiated executive and enterprise experiences. You will shape the experience thesis, build and test the first version, and help determine whether the work should become part of a broader repeatable program, remain bespoke, or stop. This role focuses on incubation: developing new experiences, strengthening consequential customer moments, and creating the principles and materials needed for durable ownership. Your initial focus will be helping bring a new flagship, hands-on enterprise customer experience to life in San Francisco, developing new executive and practitioner formats around it, and supporting selected strategic-account interventions where a differentiated approach is needed. This is a senior, hands-on individual-contributor role for a builder who combines customer and commercial judgment with original program design and excellent execution. You will work across Sales, Product Marketing, Product, Research, Solutions, Design, Events, Operations, regional marketing, and executive teams. You will be expected to make clear choices, build directly, and stay close to the work until the model is proven and ready for durable ownership. This role is based in San Francisco. We use a hybrid model of three days in the office each week and offer relocation assistance. Given the nature of the work, periods of more intensive onsite participation are expected

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 to ship AI products. THE ROLE Baseten is building its own GPU infrastructure for large-scale inference. As we move into large scale, high-density NVIDIA systems, the hardest failures are intermittent, cross-layer, and difficult to prove: RoCE congestion, InfiniBand stalls, ECN/DCQCN mis-tuning, bad optics, RNIC issues, host kernel stalls, GPU driver problems, and workload symptoms that look like network problems, but are not. We are hiring a Lead Software Engineer to build a first-class observability and root-cause analysis system for GPU fabrics. This is a hard distributed systems problem, not a dashboarding problem. The system will collect high-volume signals from switches, hosts, active probes, and inference services; reduce and correlate them in real time; understand topology and service ownership; and produce actionable diagnosis while an incident is still unfolding. This role sits at the boundary between networking and inference software. RDMA data paths, GPUDirect transfers, prefill/decode disaggregation, KV cache movement, request routing, and workload backpressure can all create fabric symptoms or hide real fabric failures. The goal is to tell an operator, quickly and with evidence, whether an incident is caused by the fabric, host, NIC, GPU, RDMA path, scheduler, or serving layer — and what to do next. EXAMPLE INITIATIVES Real-time telemetry engine — Build the ingestion, reduction, storage, and query path for high-cardinality fab

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 to ship AI products. THE ROLE We’re hiring a People Business Partner to support our team during a critical phase of growth. This is a highly strategic, high-impact role for someone who has partnered closely with leadership teams and helped organizations scale with intention. You will be deeply embedded with managers, bringing clarity and rigor to how teams are structured, how leaders operate, and how talent is developed across the organization. You’ll help shape team effectiveness, identify critical talent gaps, drive talent and performance strategies that enable high-performing teams, and build the people practices and change management approaches that allow us to scale with both speed and discipline. This role requires strong business judgment and the ability to operate with deep context. You’ll partner closely with leaders to navigate complex organizational decisions, anticipate challenges before they surface, and bring a clear point of view on what great looks like at every level of the organization. RESPONSIBILITIES Strategic partnership to leadership Serve as the trusted people partner to leadership, maintaining deep business context and translating it into people priorities by proactively surfacing systemic issues, risks, and opportunities before they become urgent. Bring data-driven insights to advise management on org design, succession planning, performance, retention, and engagement. Build management capacity across the org, equ

About the Role In this role, you’ll lead and evolve the design system foundations for ChatGPT. You’ll make nuanced design judgment explicit and usable across product teams, establishing the principles, patterns, and standards that enable coherent, high-quality experiences at scale. A paramount part of this role is raising OpenAI’s craft bar. This work extends beyond maintaining a component library: you’ll define what excellent product design looks and feels like, establish clear guidance for choosing and applying interface patterns, and ensure that new ChatGPT experiences strengthen a coherent system across platforms. Working closely with research, engineering, product, and design, you’ll create a continuous learning loop between design principles, product experiences, evaluation, and evolving technology—shaping a system that becomes more capable and expressive as ChatGPT grows. This role is based in our San Francisco HQ. We offer relocation assistance to new employees. In this role you will: Define an exceptionally high standard for craft and taste, translating that standard into principles, guidance, and examples that elevate the quality of ChatGPT. Own and evolve ChatGPT’s design foundations, including typography, sizing, spacing, layout, motion, accessibility, and responsive behavior. Establish a shared source of truth across platforms and improve the systems connecting tokens, components, patterns, widgets, learning experiences, and app-like product experiences. Build a comprehensive design systems framework with clear, opinionated guidance about when and how product teams should use different interface patterns. Translate design judgment into durable standards and use prototyping and evaluation workflows to test experiences, identify recurring issues, and improve the system. Identify promising patterns across emerging product experiences and turn them into reusable, documented foundations. Partner with research, engineering, product, and design to evolve the d

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role You’ll own the hands-on and automation work that brings WAN, fiber, carrier, and cloud-interconnect circuits into service. Partner with network engineers, fiber providers, cloud service providers, colocation teams, and data-center technicians to move each connection from ordered and patched to verified, stable, and ready for handoff. You’ll own Layer 1 troubleshooting and circuit bring-up while building workflows that translate reliable system or model output into precise, approved technician actions, capture field feedback, and drive each connection to a green-port handoff. The right person combines strong physical-networking judgment with practical automation skills: patch-panel and port mappings, optics and light levels, provider coordination, structured operational data, API or scripting workflows, and human-in-the-loop LLM tooling. Responsibilities Own Layer 1 activation and restoration for carrier circuits, dark fiber, wavelengths, Ethernet handoffs, and dedicated cloud interconnects across data centers and points of presence. Reconcile complete A-side/Z-side as-builts: circuit IDs, LOAs/CFAs, carrier demarcations, MMR/ODF/MDF and patch-panel positions, fiber pairs, cross-connects, optics, and device ports. Investigate no-light, low-light, wrong-port, link-flap, and error-rate issues across providers and CSPs; isolate continuity, dirty connectors, polarity, incorrect patching

About the Team The Monetization team is a cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across OpenAI’s ads products. This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Sc

About the Team ChatGPT is evolving from answering questions to becoming a deeply personalized assistant that helps people discover, create, and make decisions across everyday life. We're building new multimodal product experiences that combine language, images, personalization, and interactive interfaces to help millions of users accomplish tasks in entirely new ways. This team sits at the intersection of AI research, product engineering, design, and consumer experiences. We move quickly, ship frequently, and work on products that define how people interact with AI every day. About the Role We're looking for exceptional full stack product engineers who love building polished consumer experiences from the ground up. You'll work across frontend, backend, AI-powered workflows, and rich interactive interfaces to create new product experiences that blend conversation, visual understanding, personalization, and commerce. You'll collaborate closely with designers, researchers, product managers, and model teams to rapidly prototype, launch, and iterate on experiences used by millions of people. This is an opportunity to help invent entirely new interaction paradigms—not just build traditional web applications. In This Role, You Will Design and build end-to-end product experiences across web services, APIs, and modern frontend applications. Partner closely with product, design, and research to rapidly prototype and launch new AI-native experiences. Build intuitive, performant interfaces that make advanced AI capabilities feel simple and delightful. Develop scalable backend systems that power personalized, real-time product experiences. Work with multimodal capabilities including text, images, and interactive UI components. Iterate quickly using user feedback, experimentation, and product metrics. Help define engineering standards, architecture, and technical direction for a fast-growing product area. You Might Thrive If You Have significant experience building consumer-facin

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 Our Applied team brings OpenAI technologies to consumers and businesses around the world. We collaborate across research, engineering, design and business functions to turn cutting-edge AI advancements into impactful real-world applications. Our team has been behind notable product launches ( ChatGPT , API , Sora ), creating tools that help developers write code, enable businesses to operate more efficiently, and empower individuals to learn and create. As AI capabilities rapidly evolve, we focus on ensuring that our products are safe, accessible, and beneficial to all. About the Role As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as our products reach millions of users and businesses worldwide. We are focused on aligning both research and product development to drive measurable impact for these individuals and organizations alike. You should expect to define our north-star metrics, design A/B tests, and establish source-of-truth dashboards that the entire company can use to answer their own product questions. Most importantly, you should expect to be a core member of the product development team. This role is based in San Francisco, CA or Seattle, WA. 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: Embed with the product development team as a trusted partner, uncovering new ways to improve the product and drive growth Define and interpret A/B tests that help answer critical questions about the impact of model and UX changes to our product Establish a data-driven product development culture by defining, tracking, and operationalizing feature-, product-, and company-level metrics Develop and socialize dashboards, reports, and other ways of enabling the team and company to answer product data questions in a self-serve way You might thrive

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences, that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers, advertisers, and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring new ad experiences into real-world systems across OpenAI surfaces at global scale, including thoughtfully integrating them into the core ChatGPT experience. About the Role We’re looking for an experienced Software Engineer to help build the creative rendering and presentation layer of OpenAI’s ads ecosystem. This is a foundational role responsible for defining how ads are structured, rendered, and delivered across different surfaces, platforms, and media types. You’ll work across the full technical stack to build infrastructure and tooling for new ad formats, including text, image, video, native, conversational, and interactive experiences. You will help ensure these formats render reliably, perform efficiently, and feel natural within the core ChatGPT experience. You’ll collaborate deeply with Product, Design, and Research to create ads experiences that are useful, high-quality, privacy-preserving, and aligned with OpenAI’s standards for safety and user trust. In this role, you will: Design, build, and