Ai Security Analyst in United States

About the Team OpenAI's Marketing team helps customers understand, adopt, and get value from OpenAI's products and platform. The SMB Ads Marketing team is building the growth engine for small and medium-sized business advertisers: helping them discover the platform, sign up, launch campaigns, understand performance, and grow spend over time. We take a data-driven approach to understanding customer needs, market dynamics, and funnel behavior. We partner closely with Product, Engineering, Data Science, Sales, Partnerships, Marketing Operations, Design, and Communications to create a cohesive end-to-end advertiser experience and help businesses unlock value from OpenAI's advertising platform. About the Role We are hiring a Growth Marketing Manager, SMB Ads to help build and execute high-velocity growth programs for small business advertisers. This person will work across acquisition, activation, lifecycle, and conversion, with an initial focus on helping advertisers move from interest and sign-up to first meaningful spend & retention over time This is a hands-on growth role for someone who loves turning ideas into shipped experiments. You will build campaigns, lifecycle journeys, landing page tests, messaging tests, audience experiments, AI-assisted workflows, reporting improvements, and practical conversion programs. As the SMB Ads business grows, this role may continue to support acquisition and activation and expand deeper into same-store growth, lifecycle, retention, and repeat spend. In This Role, You Will: Execute growth experiments across acquisition, activation, lifecycle, and early retention. Build email, in-product, landing page, audience, messaging, and offer tests that help SMB advertisers reach first spend and repeat value. Use AI tools to prototype marketing assets, automate workflows, analyze funnel data, generate creative variations, and build internal growth systems. Partner with Growth, Product, Engineering, Data Science, and Marketing Operations

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a

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 a Quantitative Intelligence Analyst , you will focus on discovering novel and emerging risks in complex human–AI systems before they are well-defined, measurable, or widely understood. You will use deep subject matter expertise and quantitative tooling to surface weak, early, and unconventional risk signals. You will build analytic models that explain how harms could emerge and translate ambiguous patterns into structured, data-driven insight. Your work will help identify potential gaps in policy or coverage and operationalize previously unmeasured problems into signals that can support detection, mitigation, and planning downstream. You will develop analytical frameworks that map how new risks form, evolve, and propagate as products change, policies shift, and external events unfold. Your analyses will directly inform strategic risk prioritization and planning across the company, with regular visibility through strategic risk products. This role is based in office (hybrid, 3 days/week). Relocation support is available In this role, you will: Discover and define new quantitative risk signals where no established metrics exist, using subject matter exp

About the Team OpenAI’s Pricing team sits at the center of product, go-to-market, finance, and strategy. We define how OpenAI packages, prices, and scales access to our products across consumer, SMB, and enterprise customers, turning deeply technical product usage and market signal into company-level decisions. We’re looking for a senior Data Scientist to be the first dedicated data science hire on the Pricing team. This is a rare zero-to-one role with direct exposure to OpenAI’s CFO, Head of Pricing, and senior leaders across Product and GTM. You will help build the analytical foundation for pricing at OpenAI, shape executive decisions, and define what excellent pricing data science looks like. About the Role As a founding Data Scientist for Pricing, you will design the analyses, models, experiments, and decision frameworks that guide pricing strategy across OpenAI’s business. You’ll work side-by-side with the CFO, Head of Pricing, and senior leaders across Product and GTM on ambiguous, high-leverage questions where simple reporting is not enough, translating customer behavior, product usage, revenue outcomes, and market dynamics into clear recommendations. This role combines hands-on technical depth with executive-ready storytelling. You should be excited to build from first principles, operate with high independence, and influence decisions that shape how OpenAI grows and serves customers around the world. In This Role, You Will Serve as a senior analytical partner to the CFO, Head of Pricing, Product, and GTM leaders on pricing and monetization decisions. Build the analytical foundation for pricing across consumer, SMB, and enterprise segments, from exploratory analysis to repeatable decision systems. Design and execute analyses that connect customer behavior, product usage, conversion, retention, revenue outcomes, and pricing strategy. Develop models, algorithms, experiments, and decision frameworks for complex pricing, packaging, discounting, and willingness-t

By applying to this role, you will be considered for Research Engineer roles across all teams at OpenAI. About the Role As a Research Engineer here, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed. The most outstanding deep learning results are increasingly attained at a massive scale, and these results require engineers who are comfortable working in large distributed systems. We expect engineering to play a key role in most major advances in AI of the future. We expect you to: Have strong programming skills Have experience working in large distributed systems Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms 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, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment

About the Team The Personal AGI team seeks to empower all of humanity to benefit from frontier intelligence in whatever way they choose. We are responsible for training models to deploy to millions of users globally via ChatGPT, the API, and future products. We aim to evolve ChatGPT from a chatbot to an infinitely capable and personalized superassistant supporting human flourishing. We work on defining, measuring, and improving capabilities across the training stack. Our focus areas include but are not limited to model behavior, personalization, safety, factuality, instruction following, personality, interactivity, multilingual fluency, world interaction, and bringing agents to everyone. We chart the course for what to strive towards. We partner closely with research and product teams across the company ensuring that our models are safe, efficient, and reliable. About the Role You’ll work as a Research Engineer / Scientist on the North Stars team within the broader Personal AGI research org. You will work on bringing the next generation of AI-enabled experiences to all of humanity by closing the capability overhang between power users and the average consumer, including areas like tool-use, feature discovery, connectors, and instruction following. You will think deeply about the current bottlenecks in model behavior, translate these insights into robust evals, training data, reward signals, and model and harness improvements. We're looking for individuals with strong ML engineering skills and research experience passionate about creative, product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modelin

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe our research will eventually lead to artificial general intelligence, a system that can solve human-level problems. The social team helps bring OpenAI’s work to people around the world, translating complex ideas into clear, accessible, and timely content and stories across platforms. The team supports OpenAI’s mission by helping people understand how to use AI in practical, meaningful ways, while clearly and authentically communicating our technology, values, and approach to safely building powerful AI. About the Role Do you want to be one of the people behind the @ChatGPT handle on Linkedin? We’re looking for a smart and accomplished Social Media Manager (IC) to drive and manage long-tail evergreen educational social content primarily around OpenAI products on Linkedin and YouTube from the @ChatGPT and @OpenAI accounts. This role sits at the intersection of AI, education, product storytelling, and social media. You'll help shape how people around the world understand and adopt one of the fastest-growing technologies in history. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week. In this role, you will Work closely with cross-functional teams to brief and create evergreen content related to OpenAI products like ChatGPT and Codex Craft and execute social strategy and content to encourage and sustain product adoption Partner with product, marketing, and creative teams to develop educational social content that helps people understand and adopt OpenAI products. Monitor and report on product usage trends and conversations across social Balance the requests of many teams while ensuring content goes out accurately and on time Synthesize and communicate complex topics in clear language tailored for different audiences You might thrive in this role if you 7+ years of professional experience in social

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

About the Team OpenAI’s API Platform organization builds the products and infrastructure that help first-party and third-party developers build with OpenAI models. We ship the API primitives, tools, SDKs, documentation, playgrounds, and platform experiences that make OpenAI’s capabilities reliable, understandable, and useful in production. The API Experience team is focused on the end-to-end developer experience for the OpenAI API. We own the surfaces developers touch every day: docs, SDKs, the Playground, examples, onboarding flows, and the systems that help developers go from first request to production deployment quickly and confidently. About the Role We’re looking for full stack and frontend engineers to help define and build the next generation of OpenAI’s developer experience. In this role, you’ll work across frontend product surfaces, backend systems, SDK and documentation pipelines, and API workflows that serve millions of developers and companies. You’ll partner closely with product, design, research, API engineering, and developer-facing teams to make complex AI capabilities simple to understand, easy to test, and safe to launch in real-world applications. This is a highly cross-functional role for someone who cares deeply about craft, developer empathy, reliability, and product velocity. In this role, you will: Build and scale developer-facing products including the OpenAI API Playground, documentation experiences, onboarding flows, examples, and API workflow tools. Own full stack projects end to end, from product definition and UX collaboration through backend implementation, launch, measurement, and iteration. Improve the systems that generate, maintain, and publish SDKs, API references, docs, guides, and developer examples. Partner with API, research, design, and infrastructure teams to bring new model capabilities and API primitives to developers in a clear, usable way. Use developer feedback, product analytics, and direct customer insight to identif

About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. This role sits on a new team within USRO focused on building operational capacity for new, ambiguous, or fast-moving areas of work. The team helps define what needs to be built, creates the operating model to support it, and works with partner teams to make the work scalable and durable over time. As a Strategic Operations Lead, you will focus on large, cross-functional initiatives that require clear thinking, technical fluency, strong execution, and the ability to bring structure to undefined problems. About the Role We are seeking a Strategic Operations Lead to drive new and existing strategic operating builds across User Safety & Risk Operations. This is a senior IC role for someone who can turn broad, undefined priorities into clear operating models, launch plans, requirements, stakeholder alignment, documentation, reporting, and execution rhythms. This role will often support initiatives where OpenAI is developing new products or partnerships and the operating model is still being defined. These programs have a direct user safety and risk nexus because new deployment models can change what signals OpenAI can see, who owns response decisions, and how user-impacting risks are detected, escalated, and resolved. You will clarify what OpenAI owns, what partner teams own, what signals we can reliably monitor, how issues should be escalated, and how the workflow should evolve from launch support into a durable operating model. The right person is highly strategic and deeply practical. They can move from executive-level framing to detailed workflow design, stakeholder management, SOPs, launch readiness, ri

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'll: Create ambitious RL environments to push our models to their limits, and measure frontier

About the Team OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. About the Role OpenAI is seeking a System Performance Engineer to profile, benchmark, and optimize performance across our embedded hardware products. In this role, you will work across operating systems, applications, camera and vision, graphics, and platform teams to define product KPIs, build performance tooling, and drive optimizations from early lab characterization through product launch and real-world usage. You will help establish the performance standards that shape the user experience of our products, ensuring they remain responsive, efficient, and reliable throughout their lifecycle. This role requires deep expertise in embedded or high-performance systems, strong operating systems fundamentals, and hands-on experience debugging under tight latency, power, and memory constraints. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. In this role, you will: Develop system performance benchmarks, methodologies, and policies to evaluate end-to-end product behavior. Profile and analyze performance across key product use cases and workloads using custom and industry-standard profiling tools. Partner closely with engineering teams to identify bottlenecks and drive performance optimizations across the software stack. Define high-level product KPIs and establish measurement frameworks to measure launch readiness and monitor performance throughout the product lifecycle. Measure, re

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, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. 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.

By applying to this role, you will be considered for Research Scientist roles across all teams at OpenAI. About the Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We expect you to: Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms 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, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for