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About the Team OpenAI’s Agentic Data Science team helps shape how AI agents are built, deployed, and improved across our products. We partner with product, engineering, research, and security teams to define meaningful measures of success, understand how our systems behave in the real world, and translate evidence into better decisions. As AI agents become more capable, they can write and execute code, access sensitive systems, and complete increasingly complex tasks with greater autonomy. These capabilities create powerful opportunities to improve cybersecurity, but they also introduce risks that traditional security tools and processes were not designed to address. Meeting this moment requires new ways to measure security, evaluate defenses, and distinguish genuine risk reduction from friction that slows users down. About the Role We are looking for a senior data scientist to help define what effective cybersecurity looks like in the age of AI agents. You will work across OpenAI’s Security organization and cybersecurity product teams to measure emerging risks, improve internal security controls, and shape AI-powered security products. The problems are foundational: How do we know whether an agent’s security controls are effective? Which safeguards meaningfully reduce risk, and which create unnecessary friction? When an AI system identifies a potential vulnerability, how do we determine whether the finding is accurate, actionable, and ultimately resolved? How do we detect anomalous behavior or risky access when the systems themselves are changing rapidly? You will report into Data Science while partnering closely with Security, Cyber Product, Engineering, and Research. This is a high-ownership role for someone who can establish a new analytical discipline, operate across organizational boundaries, and turn ambiguous security challenges into measurable improvements. In This Role You Will Define how we measure AI-agent security. Establish metrics and evaluation frame

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role operates on a hybrid schedule requiring two days of in-office collaboration per week. The position can be based in either our San Francisco office or our new New York City office. About the Role We are looking for a Sr. Manager, Brand & Content to help build and scale Taskrabbit’s brand and content engine. This role will play a critical part in shaping how Taskrabbit shows up to clients, Taskers, partners marketing across channels, translating our brand platform into a cohesive, always-on content system that drives awareness, engagement, and long-term demand. This is more than a traditional content role. You will define what we say, how often we show up, and how our narrative comes to life across marketing channels. You will work cross-functionally with Creative, PR, Social, Growth, CRM, SEO, and regional teams to ensure we are delivering consistent, high-quality storytelling that resonates with our audiences and

About the team OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. In support of that mission, the ChatGPT Ads team is building advertising products that help businesses reach customers in useful, trusted, and responsible ways. The Ads Strategy, Planning, and Operations team is responsible for building the operating foundation for OpenAI's advertising business: GTM systems, segmentation, coverage, planning, forecasting, business rhythms, sales programs, incentives, and scalable execution across advertisers, agencies, partners, resellers, and internal teams. This team sits at the intersection of Sales, Product, Engineering, Finance, Legal, Policy, Marketing, Partnerships, and Customer Success. About the role We’re looking for a Sales Strategy & Operations Lead to help build the GTM operating system for ChatGPT Ads. This person will work across sales strategy, planning, systems, segmentation, forecasting, operating rhythm, sales programs, and commercial execution to help the Ads business scale with clarity, speed, and control. This role is for someone who can move between strategy and execution: able to define operating models, build analytical frameworks, run cross-functional planning processes, improve GTM systems and data quality, and program manage high-priority sales initiatives. The ideal candidate has meaningful experience in digital advertising, media, adtech, marketplace, or platform businesses and understands the complexity of scaling sales motions across direct sales, agencies, partners, resellers, outsourced channels, and self-serve. In this role, you’ll: Help build the operating foundation for ChatGPT Ads across GTM systems, segmentation, coverage, forecasting, sales planning, and business reviews. Partner with Sales, Ads Ops, Product, Engineering, Strategic Finance, Legal, Policy, Marketing, Partnerships, Customer Success, and Data teams to translate strategy into execution. Develop objective frameworks for ac

About the Team The SaaS and Software Governance team sits within Corporate IT and helps OpenAI scale from startup-speed tooling to mature enterprise architecture. The team owns practical governance for software, SaaS, integrations, APIs, identity, data access, and agent-enabled workflows, with a mandate to improve security, reduce software sprawl, and help business teams move faster through better foundations. About the Team OpenAI is scaling from an emerging, high-velocity startup into a mature enterprise operating model. The IT Software Architect will help shape the software, SaaS, Data integration, and agent-enabled architecture that lets the company move quickly while improving security, compliance, data quality, and customer, partner, and employee experience. This role is not a traditional ivory-tower architecture function. It is a hands-on governance and enablement role that partners with business teams, IT operations, Security, Procurement, Business Platforms, Applied teams and Data Engineering to guide software decisions, reduce unmanaged sprawl, and build reusable enterprise foundations. Why This Role Matters OpenAI’s software footprint is expanding rapidly across SaaS, internally built tools, agents, integrations, APIs, third-party platforms, and application systems that OpenAI. The company needs a stronger tools architecture layer that can help teams make good decisions early, avoid duplicate tools, govern sensitive data and identities, and identify where OpenAI should build instead of buy. The person in this role will help turn software governance from an approval checkpoint into an enterprise capability: a system that improves speed, reliability, security, and business outcomes. What You'll Do Own the target architecture for enterprise software, SaaS, integrations, APIs, and agent-enabled business systems across Corporate IT. Drive deprecation and consolidate targets for enterprise software. Build lightweight governance patterns that guide teams before

About the Team Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. Mitigating the frontier risks resulting from these capabilities is paramount to OpenAI’s ability to continue deploying models safely. The Preparedness team is dedicated to addressing these critical risks. Our work includes: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse and misalignment safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the Role We are seeking exceptional researchers who can push the frontier of safety mitigations. You will help derisk frontier models by developing novel safety mitigations, developing and applying new techniques from domains like interpretability, control, and alignment to ensure the safety of OpenAI’s deployed models. You will play a critical role in defining how a safe AI system should look in the future at OpenAI, making a significant impact on our mission to build and deploy safe AGI. This role requires strong technical depth and close cross-functional collaboration to ensure our safety mitigations are enforceable, scalable, and effective. We seek researchers who can partner with experts across domains such as misalignment, cybersecurity, and biology in order to develop the best possible end-to-end safety stack. In this role, you will: Work on identifying emerging AI safety risks and new methodologies for exploring and mitigating the impact of such risks Build (and then continuously refine) the evaluations that enable us to assess the extent of these risks; this might include worki

About the Team Equity Administration at OpenAI is responsible for the operational foundation of our equity programs. Our team ensures equity data and reporting are reliable, our systems and integrations are resilient, and our processes and controls are built to scale globally. We work cross-functionally with Legal, Finance/Accounting, Payroll, Tax, People, and key vendors to uphold compliance requirements and enable equity strategy as the company evolves. About the Role We’re looking for an experienced Senior Manager, Global Equity Administration to lead the end-to-end equity program for a subsidiary, with a focus on high-quality execution, scalable processes, auditable controls, and reliable equity systems. You will be hands-on in day-to-day equity administration and help improve how we operate as we scale. You will report to the Head of Equity Administration and partner closely with Legal, Equity Programs, Compensation, Tax, Payroll, and Finance to ensure equity operations are accurate, timely, and employee-friendly. Location: 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: Execute end-to-end employee equity administration across key lifecycle events (new grants, vesting/RSU releases, option exercises, and related transactions). Run recurring operational cycles by managing timelines, checklists, stakeholder inputs, and issue resolution. Produce audit-ready equity reporting and support accounting, compliance, and reporting needs with accurate, well-documented data. Build and maintain automated reporting (scheduled reports, dashboards, reconciliations) to reduce manual effort and improve speed and accuracy. Support equity system operations (Shareworks or comparable) including troubleshooting, configuration updates, permissions, report builds, and workflow maintenance. Partner with Internal Controls to keep process documentation, narratives,

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 Trusted Computing and Cryptography is a core security team at OpenAI focused on deploying high-performance cryptography at scale, secure key management, and trusted hardware enclaves—from boot measurements to GPU confidential computation. As a Hardware Platform Security Architect, you’ll own hardware platform security at OpenAI. In this role, you will: Co-Architect Secure Silicon: Collaborate with cross-functional silicon teams (Silicon Design, DV, FW) and silicon partners (silicon test facilities, foundries) to develop secure silicon that meets the end-to-end system requirements. Co-Architect Secure Hardware: Collaborate with hardware vendors and cross-functional teams (kernel, compiler, infra) to design secure hardware that meets performance and security needs. Co-Architect Secure Systems: Architect and deploy systems using TPM2, Secure Boot, Nitro Enclaves, Intel SGX, AMD-SEV, and other secure hardware technologies. Drive Innovation: Engage with internal and external partners to align hardware innovations with OpenAI’s trusted computing and cryptographic requirements. You might thrive in this role if you have: 10+ years of industry experience in hardware security or hardware–software co-design. Proven expertise in deploying secure hardware systems at scale and integrating secure hardware primitives. Strong coding skills in Rust and/or C/C++, with proficiency in Python. Proven ability to collaborate across teams, architect solutions,

About the Team The Core Models team helps shape how OpenAI’s frontier models are built, measured, and launched. We work across Research, Engineering, Model Design, Data Science, and Product to turn advances in model capabilities into reliable, useful experiences for people. Our scope includes model planning and launches as well as building data flywheels, evaluations and measurement systems to ensure our models have strong capabilities and behavior. About the Role As a Product Manager for the Core Models team, you'll be at the forefront of defining and guiding the future of how our AI models work in real-world applications. You will connect user needs to model and systems decisions: how prompts are understood; how information is aggregated and made useful for training and evaluation data; and how capabilities move from research prototypes into the mainline model and launch stack. You will operate comfortably across research, infrastructure, and consumer product surfaces, creating clarity where ownership and technical boundaries are still emerging. 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: Translate user and product goals into clear model requirements, system architecture choices, and research priorities across query understanding, indexing, retrieval, ranking, tool boundaries, data, training, inference, and evaluation. Build closed learning loops that turn product usage, explicit feedback, and other user signals into datasets, evaluations, experiments, training priorities, and launch decisions. Define success across offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost. Partner closely with post-training research, applied product engineering, Model Design, and Data Science to integrate capabilities into the mainline model stack. Create reusable platforms and operatin

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

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 while managing risk responsibly. The Procurement Operations team supports the operational flow of purchasing across OpenAI, helping teams turn business needs into complete, policy-aligned, and executable procurement activity. We partner across Procurement, Finance, Legal, Security, Accounting, Accounts Payable, Systems, and business teams to improve how requests, suppliers, purchase orders, approvals, data, documentation, and downstream handoffs move through our systems. As OpenAI scales, we are building procurement operations that can absorb increasing complexity without adding unnecessary friction. That means using AI thoughtfully, simplifying where we can, strengthening operating discipline where we must, and continuously improving how our stakeholders experience procurement. About the Role We are hiring two Senior Managers, Procurement Operations to manage the operational backbone of how OpenAI turns requests into committed, controlled, and payable spend. One role will focus on Technology categories, and the other will focus on Corporate Services categories. These roles are not removed from the work. You will be expected to review requests in the system, make or guide request and PO updates, resolve operational issues, and use that firsthand view to identify what needs to change. You will push the envelope without losing the thread on risk, staying close enough to the details to understand where friction, ambiguity, and control gaps show up. You will help improve procurement outcomes across intake, purchase requests, PO quality, supplier coordination, approval workflows, documentation, service delivery, and downstream financial handoffs. You will oversee and improve oper

About the Team The ChatGPT Model Flywheel team unified goal is to transform model advancements into great ChatGPT user experiences through reliable serving, rapid experimentation, safe deployment, and continuous improvement. Team Focus Areas Model Experimentation: Enable rapid, safe model validation for ChatGPT and Codex products through experiment automation and lifecycle management. Model Deployment: Ensure safe, scalable deployment of model capabilities with robust rollout and operational tooling. Automate capacity management and incorporate platform-wide health monitors. Model Measurement: Build comprehensive evaluation and measurement systems for model quality, from user signals to launch scorecards. Improve end-to-end feedback loops for continual model improvement. Key Partnerships Collaborate cross-functionally with teams including Model Measurement DS, Research, Codex, Fleet, Inference, and API. In this role, you will: Elevate and consolidate ChatGPT’s harness, context management, and system prompt frameworks. Drive expansion and improvement of multi-tier model experiences. Support and scale self-serve experiment capabilities and automated guardrails. Lead model rollout automation, capacity management, and health monitoring. Shape end-to-end measurement systems (evals, grader signals, user feedback, etc.). You might thrive in this role if you have: Proven experience leading engineering teams in complex, cross-functional environments. Demonstrated success shipping production systems at scale (ideally for AI or large backend services). Deep understanding of model-driven product development, deployment lifecycle, and measurement tooling. Excellent communication and collaboration skills—experience interfacing directly with engineering, research, and product stakeholders. Prior involvement with large language models, distributed infrastructure, or experimentation platforms is a plus. Why Work With Us Tackle highly impactful technical challenges at the cutting edg

About the Team The Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and 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 Safety Research team aims to fundamentally advance our capabilities for precisely implementing robust, safe behavior in AI models, and to leverage these advances to make OpenAI’s deployed models safe and beneficial. This requires a breadth of new ML research to address the growing set of safety challenges as AI becomes more powerful and used in more settings. Key focus areas include how to enforce nuanced safety policies without trading off helpfulness and capabilities, how to make the model robust to adversaries, how to address privacy and security risks, and how to make the model trustworthy in safety-critical domains. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. About the Role OpenAI is seeking a senior researcher with passion for AI safety and experience in safety research. Your role will set directions for research to enable and empower safe AGI and work on research projects to make our AI systems safer, more aligned and more robust to adversarial or malicious use cases. You will play a critical role in shaping how a safe AI system should look like in the future at OpenAI, making a significant impact on our mission to build and deploy safe AGI. In this role, you will: Conduct state-of-the-art research on AI safety topics such as RLHF, adversarial training, robustness, and more. Implement new methods in OpenAI’s core model training and launch safety improvements in OpenAI’s products. Set the research directions and strategies to make our AI systems safer, more aligned and more robust. Coordinate and collaborate with cross-functional team

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team The GTM Data Science team partners with Go-to-Market, Technical Success, Product, Engineering, RevOps, and Strategic Finance to build the shared intelligence layer for OpenAI's B2B business. The team turns product usage, customer behavior, revenue, field activity, and customer feedback into rigorous insight products that help leaders and field teams understand where customers are succeeding, where adoption is blocked, and what actions will accelerate durable growth. We are building systems that make customer intelligence proactive: surfacing risk, expansion potential, product gaps, and repeatable playbooks before they show up as escalations or missed opportunities. About the Role As the Applied Data Science & Insights Lead for GTM Intelligence Solutions and Technical Success, you will be a hands-on technical leader responsible for shaping how OpenAI measures, understands, and improves customer adoption across our B2B products. You will build AI/ML-powered intelligence products that connect account health, product usage, customer lifecycle, support tier, qualitative sentiment, commercial context, and field actions into a practical operating system for GTM and Technical Success. This role will build the data science foundation for Technical Success: defining the metrics, models, operating insights, and decision systems that help the team scale customer adoption and expansion with rigor. You will also be expected to build and lead a small mighty team over time: setting direction, hiring and developing talent, creating operating cadences, and holding a high bar for technical rigor and business impact. You will lead the development of models, metrics, and decision systems that recommend what GTM and Technical Success teams should do next, explain why, and measure whether those interventions worked. Your work will help customers move from pilots to production, deepen usage across products, identify high-value use cases, reduce churn risk, and create a f