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About the Team The Workload Networking team is responsible for the collective communication stack used in our largest training jobs. Using a combination of C++ and CUDA we work on novel collective communication techniques that enable efficient training of our flagship models on our largest custom built supercomputers. The models we train are key ingredients to the AI research progress at OpenAI and the field as a whole, and we continually incorporate learnings from our entire research org into our training platform. About the Role As a Software Engineer, Networking you will design and implement custom networking collectives that are tightly integrated into our training stack. We’re looking for people who have a background in low level performance critical software. Experience with collective communication is a bonus. 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: Collaborate closely with ML researchers to design and implement efficient collective operations in C++ and CUDA. Ensure that our largest training jobs take full advantage of the different network transports used in our supercomputers. Work on simulations to inform our future supercomputer network designs. You might thrive in this role if you: Have written distributed algorithms using RDMA in the past. Are comfortable writing low level performance sensitive CPU and/or GPU code. Are familiar with network simulation techniques. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voic

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, meas

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Create ambitious RL environments to push our models to their limits, and measure frontie

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day. About the Role As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements. We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations. This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full trai

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments that improve scaling of compute on context. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures,

About the Team The B2B Marketing team contributes to OpenAI's broader mission of ensuring responsible and widespread adoption of artificial intelligence. We are responsible for developing and executing strategies that drive awareness, engagement, and usage for OpenAI's products and platform. We take a data-driven approach to understand our customers' needs and challenges, ensuring that their voices are reflected in product development and messaging. We then partner closely with Product, Engineering, Growth, Sales, Research, Comms, and Design teams to create a cohesive customer experience across all our channels. About the Role We're looking for a senior product marketing leader to own the strategy, narrative, and go-to-market direction for ChatGPT Work. This role will help define how professionals, teams, and organizations put AI to work on meaningful tasks, move from questions to completed work, and adopt new ways of working across their business. You will serve as the senior product marketing owner for ChatGPT Work, shaping the category, setting portfolio priorities, and connecting product innovation to customer understanding, adoption, and growth. Your scope will span the Work experience across surfaces, connected tools, and AI-powered workflows, with a clear focus on the needs of professional users, Business customers, and Enterprise organizations. This is a leadership role for someone who can set strategy, make difficult tradeoffs, and stay close enough to the work to shape the messaging, product decisions, launches, and programs that determine whether customers adopt. You will partner with Product, Growth, Sales, Research, Comms, Creative, and adjacent product marketing teams to build a coherent experience from first discovery through sustained team usage. In this role, you will: Own the ChatGPT Work product marketing strategy: Define the audience, market opportunity, positioning, competitive strategy, and go-to-market priorities across professional users, tea

About the Team OpenAI is building Procurement of the future: one that uses AI-enabled systems, clean data, and scalable processes to help the business absorb increasing complexity, speed, volume, and throughput — while enabling teams across OpenAI to operate more strategically and at greater scale. The Hardware Procurement Operations team supports the operational flow of goods and hardware purchasing across OpenAI's hardware business units. We help teams turn business needs into controlled, accurate, and executable procurement activity, from request intake through purchase orders, supplier coordination, change management, receiving readiness, and downstream invoice support. As OpenAI scales, we are building procurement operations that can support changing hardware needs, new business unit priorities, and increasing operational complexity. That means creating practical standards where they help, preserving flexibility where the business requires it, and continuously improving how requests, suppliers, POs, data, and controls move through our systems. About the Role As a Senior Manager of Procurement Operations focused on Hardware, you will own procurement operations for one or more assigned hardware business units. You will be the day-to-day DRI for hardware and goods procurement activity, leading work from intake through purchase requests, POs, supplier needs, changes, receiving readiness, and operational escalations. This is a hands-on operator-builder role for someone who understands the practical complexity of hardware and goods procurement and can both run the work and redesign how the work gets done. You will keep work moving while improving the operating model through better systems, workflows, automation, AI-enabled processes, controls, metrics, and operating leverage. You will evaluate how people, process, policy, systems, data, fiscal controls, and accounting practices come together, and you will work closely with other Central Procurement and BU Procurement

About the Team OpenAI’s Strategic Finance organization provides financial insights and guidance to support the company’s long-term strategy and ambitious growth. We partner across Product, Partnerships, Engineering, and GTM to allocate resources to the highest-impact opportunities while protecting sustainable unit economics. The Applications Technology Strategic Finance team partners closely with Product to scale core offerings and bring new products to market. We lead revenue forecasting and performance management across the product portfolio, including economic margins, pricing, and partnership deal pricing and structuring. About the Role We are hiring on our Strategic Finance Partnerships team to drive strategic decision-making across OpenAI’s growth and media partnership portfolio, focused on our consumer business. This role will be a critical finance partner to Partnerships deal leads and Product owners, responsible for evaluating, pricing, and structuring partnerships, and translating partner opportunity into decision-ready economics and performance management. The role will be hands-on in deal evaluation, negotiation support, and portfolio oversight. You will shape how OpenAI approaches partnership unit economics, measurement and incrementality, and how partnership performance is incorporated into forecasts and planning. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Own financial evaluation for growth and media partnerships, including modeling revenue, margin, compute, and payback to support decision-making and negotiations. Develop clear economic frameworks and deal guardrails (pricing floors, rev-share structures, caps, minimum guarantees, performance-based terms) to protect long-term unit economics. Partner closely with Product and Partnerships to define and measure incrementality and ensure contract terms align with measurable outcomes. Lead partnershi

About the Team The Finance Platform & Technology team at OpenAI builds and scales the future-proof systems and data architecture that power our core financial operations. We enable business agility, compliance, and operational excellence across quote-to-cash, procure-to-pay, inventory, and asset management for both B2B and B2C. Our focus is on modernizing workflows through strategic integrations, scalable automation, and seamless data flows empowering smarter decisions, reliable reporting, and sustainable growth as OpenAI evolves About the Role We are looking for a Supply Chain Transformation Architect to redesign and modernize our end-to-end supply chain operations supporting robotics, consumer hardware, and data center infrastructure. This role sits at the intersection of process, systems, and data. Your primary focus will be transforming supply chain processes across planning, procurement, manufacturing, logistics, and fulfillment—then enabling those processes with the right systems architecture, data foundation, and AI-driven automation. You will help move the organization from manual, reactive operations to intelligent, data-driven supply chain execution. In this role you will: Lead End-to-End Supply Chain Transformation Evaluate and redesign core supply chain processes across demand planning, supply planning, procurement, manufacturing operations, logistics, and fulfillment. Identify operational bottlenecks, fragmented workflows, and manual processes that limit scalability. Build standardized process frameworks and operating models that support rapid scaling of hardware programs. Drive Operational Excellence Implement structured supply chain practices such as: S&OP / Integrated Business Planning Supply risk management Inventory optimization Supplier collaboration frameworks Logistics visibility and execution models Establish operational KPIs and governance to improve predictability, responsiveness, and resilience. Architect the Digital Supply Chain Tra

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role We are seeking a Software Engineer, Security Observability to join our Security team. In this role, you will be responsible for building secure, scalable systems that enhance our security observability infrastructure. Leveraging your strong engineering skills, you will collaborate with cross-functional teams to develop, deploy, and maintain robust software solutions that support our security and detection capabilities. This role is open to remote employees, or relocation assistance is available to one of our OpenAI offices in San Francisco, Seattle, or New York City. Due to requirements associated with work this role may support, applicants for this position must be U.S. citizens. In this role, you will: Design and develop scalable software systems that facilitate security observability across our infrastructure. Build and maintain data pipelines that centralize and store security-relevant data from diverse sources. Proactively improve the resilience and reliability of data systems to ensure high platform availability Collaborate closely with Detection & Response (D&R) and other security teams to reduce the company’s security risk. Contribute to data engineering in support of forensic investigations and compliance efforts. You might thrive in this role if you have: Strong software engineering experience, with proficiency in programming languages such as Python, Golang, or similar. A background in infrastructure as code, with exp

About the Team The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors. About the Role As an Agentic Risk Analyst, you will shape OpenAI’s operating picture for current agentic risk across products and platforms. You will bring a strategic, system-level perspective to current risks, connecting individual incidents, technical findings, abuse patterns, and external developments to relevant workstreams, mitigations, owners, dependencies, and residual gaps. You will analyze how risks emerge through autonomy, multi-step task execution, tool use, memory, retrieval, connectors, computer-use capabilities, and multi-agent workflows, with a particular focus on both adversarial misuse and unintended system behavior. By synthesizing signals from investigations, evaluations, red teaming, security reviews, product launches, external research, and real-world incidents, you will maintain a current view of material risks and evolving threat patterns. Your work will help turn complex and often ambiguous signals into coordinated decisions and measurable follow-through across product, safety, security, policy, and governance teams. You will work closely with investigators, engineers, product, policy, safety, and security teams, and measurement and forecasting

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 As a Supply Chain Program Manager, you will own material readiness and supply chain execution for critical hardware programs spanning custom silicon, systems, memory, storage, networking, and rack infrastructure. You will work cross-functionally with Engineering, Strategic Sourcing, Manufacturing Operations, Finance, Planning, Quality, and external suppliers to develop and execute scalable supply strategies that support aggressive product development and deployment timelines. This role requires deep understanding of hardware supply chains, material planning, NPI execution, supplier management, and operational scaling in constrained and rapidly evolving environments. In this role you will: Material Readiness & Supply Planning - Own end-to-end material readiness across NPI and production phases, including building the necessary framework and processes for enablement. Drive supply planning and execution for long lead-time and constrained commodities including ASICs, HBM, DDR, SSDs, networking, optics, power, thermal, and mechanicals. Build and manage material readiness plans aligned to proto/pre-EVT, EVT, DVT, PVT, and mass production schedules. Monitor supply health, lead times, inventory positions, allocation risk, and capacity constraints. Drive shortage management, allocation mitigation, and recovery planning. Coordinate supply commits, forecast alignment, and supply continuity planning with suppliers and manufacturing partners. Cross-Functional Program Ma

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 Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect our model weights, customer data, and critical systems across multiple cloud environments. We partner with teams across OpenAI—Applied Engineering, Research, IT, and Security—to provide a secure and scalable platform for permissioning, orchestration, and innovative AI research. About the Role We’re looking for a Staff+ Software Engineer to help build and evolve the identity infrastructure that supports OpenAI’s research, engineering, and internal platforms. This role sits at the intersection of cloud infrastructure, identity systems, and software engineering. You’ll work across production systems, infrastructure-as-code, cloud control planes, identity providers, and operational infrastructure to build secure, scalable, and reliable systems used broadly across the company. The ideal candidate has experience building and operating large-scale, mission-critical systems with strong reliability and security requirements, and is comfortable writing production code, designing distributed systems, and driving ambiguous projects from 0 to 1 while building the operational rigor needed to run critical infrastructure over time. In this role, you will: Lead the architecture, development, and operation of identity infrastructure that spans cloud platforms, internal systems, and critical engineering services. Design and evolve systems for authentication, authorization, access governance, auditability, and policy enforcement with a strong focus on reliability, scalability, and secure-by-default design. Build foundational infrastructure and platform capabilities that are broadly used across engineering, research, and security teams. Improve the reliability, observability, performance, and op

About the Team Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters. Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale. About the Role We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks. You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training. In this role, you will Design and build a unified dataset read platform for multiple current and future training frameworks. Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable. Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts. Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late