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About the Team The Intelligence & Investigations Engineering team builds systems that detect, analyze, and disrupt abuse across OpenAI’s products. We partner closely with the Child Safety team and cross-functional groups to protect users while advancing OpenAI’s goal of developing AI that benefits everyone. About the Role As a Fullstack Engineer focused on child safety, you’ll build data-intensive, AI-powered applications and infrastructure that enable operators and investigators to work effectively and responsibly. You’ll adapt quickly in ambiguous, fast-moving environments to deliver well-crafted, reliable tooling for high-severity safety work. *Candidates should understand this role involves exposure to sensitive and egregious content. In this role, you will: 7+ years of experience as a software engineer Prototype, build, and maintain intelligence systems that detect, triage, and enable efficient human review of possible high severity harm Work hand in hand with operators and investigators, designing and delivering systems that enable them to do their work faster, more accurately, and more safely. Develop across the stack: UIs, services, pipelines, and anything else required to solve the problems we face. Interact with partners across Product Policy, Platform Integrity, Safety Systems, and Research Contribute to the team’s technical strategy, especially for child safety related tools and systems Report on impact in a data-driven fashion You might thrive in this role if you: Have a strong software engineering foundation and enjoy owning systems end-to-end—from infrastructure and data ingestion to frontend tooling Are energized by working at the frontier of AI capabilities, integrating new models and APIs into practical systems Have experience building and operating large-scale data pipelines or search/retrieval systems Are proficient in Python and/or TypeScript, and familiar with tools like Spark, Kafka, Flink, data warehouses, and SQL Take a product-minded ap

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a member of the GTM team at Anthropic, you will be a Staff Forward Deployed Engineer (FDE) who embeds directly with our most strategic customers and leads the technical direction of their AI adoption. Customers bring you in to lead, not only to implement: you decide what should be built, and then make sure it gets built well. You will work with customer teams to ship advanced AI applications that solve real world business problems, and guide the architecture and advisory work that surrounds those builds across an account. Working closely with our Research, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability. You will sit at the frontier of enterprise AI deployments and help shape our forward-deployed motion as it scales. We expect Staff FDEs to set direction under ambiguity and represent Anthropic at the highest level in customer environments. In this role, you guide architecture and build initiatives across workstreams, working directly with senior technical and business stakeholders and owning outcomes that span an account's roadmap. You don't need to have shipped agents to production. You do need deep experience building and operating production systems, hands-on time with agents, and the judgment to lead architecture and advisory work with enterprise customers. Responsibilities Own technical strategy for a key account or vertical, in partnership with accou

About the Team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments as well as other OpenAI products worldwide. We operate across the full funnel - from awareness and acquisition through activation, retention, and expansion - using a combination of global performance marketing, AI-powered workflows, in-product optimization, insights, experimentation, and creative ops engineering. Our Growth Marketing team is a rapidly scaling functional area, accelerating growth by connecting out-of-product and in-product experiences into seamless journeys that acquire, retain, and re-engage users, unlocking ChatGPT’s transformative potential in users’ daily lives. We work cross-functionally with product, engineering, design, data science, finance, and marketing to unlock scalable growth levers and deliver measurable impact across diverse markets. This team thrives on rapid testing, rigorous measurement, and creative problem solving, all while keeping user value at the center of our decision-making. About the Role In this role, you will build and run the creative and advertising operations system that powers OpenAI’s paid marketing programs. You will connect Creative and Growth Marketing teams, establish clear processes for producing and launching high-quality ads, and keep the operational details behind paid campaigns organized, accurate, and scalable. You will help translate growth priorities into creative briefs and testing roadmaps, coordinate assets and approvals across internal teams and external partners, and turn performance results into clear next steps. 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: Build and manage the end-to-end paid creative operating system , including creative intake, briefing, production, asset delivery, approvals, trafficking, launch, reporting, and iteration. Serve as the day-to-da

About the Team Our team builds classification and evaluation systems that give post-training and research teams fast, reliable feedback on model behavior. We combine machine learning and production engineering to make these capabilities accurate, efficient, and useful at scale, helping researchers assess changes and improve models and products. We work closely with research teams to develop useful measurements and make them practical to run. Our work spans classifier development, rigorous evaluation, and efficient production inference, with ownership from initial experimentation through deployment and continued improvement. About the Role We’re looking for a machine learning engineer to develop new classification and evaluation capabilities and bring them into production. You’ll help turn open-ended questions about model behavior into well-defined ML problems, build methods that address them, and establish how reliably those methods work. This role combines traditional machine learning, model evaluation, and real-time engineering. You’ll own classifiers throughout their lifecycle, including supervised fine-tuning, distillation, evaluation, deployment, and production inference. You’ll work closely with researchers to identify valuable problems and with software engineers to make promising approaches useful at scale. In this role, you will: Build, deploy, and operate production classification and evaluation systems that provide useful feedback to post-training and research teams. Optimize production inference, including model serving, batching, caching, throughput, latency, compute utilization, and cost. Train and optimize classifiers using supervised fine-tuning and distillation, validating quality and efficiency before deployment. Own the reliability and observability of deployed classifiers, diagnose production issues, and improve their performance over time. Design rigorous evaluations that assess accuracy, calibration, generalization, and potential measurement bi

About the team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments and other OpenAI products worldwide. We work across the full funnel—from awareness and acquisition through activation, retention, and expansion—using experimentation, data science, machine learning, and product engineering to help more people discover and realize durable value from OpenAI’s products. Our team partners closely with Product, Engineering, Data Science, Design, Finance, Lifecycle, and Growth Marketing. We move quickly, test rigorously, and hold a high bar for measurement, privacy, reliability, and user trust. About this role: We are looking for a Machine Learning Engineer to build the models and decision systems that optimize paid marketing investment for ChatGPT and other OpenAI products. You will develop budget allocation and control algorithms that determine where to invest, how quickly to spend, and how to adjust as performance changes. The challenge is to make reliable decisions from noisy, delayed, and incomplete signals. You will combine machine learning, optimization, and experimentation to improve incremental growth and long-term user value within budget and efficiency constraints. You will own this work from problem formulation and prototyping through deployment, evaluation, and ongoing operation. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to eligible employees. In this role, you will: Build budget allocation algorithms. Decide how to distribute investment across channels, campaigns, and markets using estimates of marginal returns, while accounting for diminishing returns, uncertainty, and business constraints. Develop spend pacing and adaptive control systems. Adjust budgets and spending rates as performance changes, balancing responsiveness with stability when feedback is delayed or noisy. Build in spend limits, monitoring, and safe fallback

Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di

Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di

Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di

About the Team The ChatGPT Space team is building a shared workspace where people and AI agents turn ideas into polished, editable work. Space brings teammates, ChatGPT, and dots together around shared knowledge and projects, with creation experiences spanning Pages, Sheets, Slides, and new kinds of artifacts. We want work to keep improving beyond the first draft, using shared context and collaboration to stay current as projects evolve. We work across product, design, and research, partnering closely with model training teams to shape how frontier models create and edit artifacts. We ship quickly, learn from real usage, and hold a high bar for craft, correctness, and speed. About the Role We’re hiring a Frontend Software Engineer to build a top-tier collaboration experience and help shape how people work with AI. This is a craft-heavy role: you’ll partner closely with design to prototype, iterate, and polish new interaction models, then turn them into reliable, high-performance product experiences. You’ll help define what great looks like for collaboration between people and agents: how shared context is represented, how contributions and changes are made understandable, and how users stay oriented and in control as work moves between teammates and AI. What You’ll Do Build and ship polished, high-performance UI for Space and its collaborative workflows. Partner tightly with design to turn prototypes into production-quality experiences, from layout and typography to motion and interaction details. Develop intuitive interfaces for creating and editing shared content, organizing project context, and reviewing contributions from teammates and AI as work evolves. Own frontend architecture decisions across component systems, state management, navigation, and rendering performance. Improve quality and reliability through testing, instrumentation, accessibility, and thoughtful UX for loading, errors, and concurrent changes. Collaborate with research, platform, and backend

About the Team Identity is the foundation of trust in an AI-powered world. As people build a rich personal and organizational context in ChatGPT, they need systems that protect it, remember it, and let them share it securely across apps and agents. Without strong identity, context stays locked away or exposed. With it, AI becomes safe, personal, and truly useful, empowering users while keeping control firmly in their hands. Our team builds the trusted OpenAI account layer that connects people, enterprises, developers, and agents to OpenAI apps and the broader AI ecosystem. Our systems are the front door to OpenAI—held to an exceptionally high bar for availability, security, and latency—and are depended on by many internal teams. About the Role As an Engineering Manager, Identity Platform you will lead a team owning foundational identity services that must be highly reliable, secure, and fast under extreme load. You’ll set direction, grow and support the team, and partner closely across engineering and security to strengthen the platform that enables trusted access to OpenAI products. In this role, you will: Build, lead, and develop a high-performing engineering team. Coach and mentor engineers and senior technical leads to increase their impact and support their growth. Define and own the technical strategy, roadmap, and execution for OpenAI’s core identity systems. Guide the architecture of distributed systems operating at massive scale, with high requirements for reliability, privacy, and performance. Partner closely with Product and Infrastructure teams to support new product needs and uphold high system standards. Ensure the team operates effectively, maintains strong engineering rigor, and consistently delivers against ambitious goals. Establish processes and a culture that enable fast learning, high trust, and responsible innovation. Lead the team responsible for the authentication stack and token exchange infrastructure, ensuring high availability, strong sec

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the role: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement ro

About the team The Monetization team is a new cross-functional group spanning engineering, product, research, and design. We are building the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to create user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen trust, expand economic opportunity, and support OpenAI’s long-term innovation. We believe monetization should deliver clear user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem for developers and businesses. The team operates in a greenfield environment, moving quickly through prototyping, experimentation, and iterative deployment. We partner closely across Product, Design, and Research to bring new capabilities into real-world systems at global scale. About the role We’re looking for an experienced Software Engineer to lead the design and development of the systems that turn advertiser feeds (eg. retail feeds, travel feeds etc.) into relevant, reliably delivered ads. In this foundational role, you will build across the full ads lifecycle—from ingesting and organizing retailer or travel catalogs into efficient retrieval systems, supporting ranking models, and serving ads at scale. This role is well suited to an engineer with direct experience in product ads retrieval, ranking, and delivery, along with a strong understanding of merchant feeds and shopping systems such as Google Shopping, YouTube product ads, or Amazon. We also welcome engineers with Senior Staff-level or greater scope who have deep ownership of large-scale catalogs, search and indexing, ads serving, or closely related distributed systems. You will independently own complex systems, make sound technical tradeoffs, and help define the architecture and roadmap for Shopping/Travel/Feed Ads. You will collaborate closely with Ads ML, Ads Delivery, Product, Design, and Research to connect accurate, fresh advertiser

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building an AI powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for Software Engineers who're passionate about blending production-ready platform architecture with new tech and new paradigms. You’ll push the boundaries of OpenAI’s newest technologies to enable interactions and automations that are not only functional, but delightful. We value proactive, customer-centric engineers who can get the foundational details right (data models, architecture, security) in service of enabling great products. In this role, you will: Own the end-to-end development lifecycle for new platform capabilities and integrations with other systems Collaborate closely with engineers, data scientists, information systems architects, and internal customers to understand th

About the Team The Plugin Developer Platform team builds the APIs, SDKs, and tools that let people extend ChatGPT and Codex. We work on plugins, connectors, the Model Context Protocol (MCP), and interactive apps. 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 covers plugin creation and publishing, the systems that run plugins across our products, and open standards that developers can build on. About the Role We’re looking for an experienced Android engineer to bring plugins, connectors, and interactive apps to life on mobile. You’ll build the Android experiences and platform foundations that help developers extend ChatGPT and help users discover and use those capabilities from their devices. You’ll work across native Android interfaces, developer-facing APIs, and the systems that support extensibility on mobile. You’ll collaborate closely with product, design, and platform engineers, owning features from early exploration through implementation, launch, and iteration. You’ll also engage directly with developers and partners to understand how their workflows translate to Android. Their experience will inform the interfaces and abstractions you build, the problems you prioritize, and the tradeoffs you make. 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: Build Android experiences for plugins, connectors, and interactive apps within ChatGPT. Develop reusable Android components and interfaces that support a growing ecosystem of developer-built experiences. Partner with platform engineers to connect native mobile experiences with APIs, SDKs, and backend systems. Work with developers and partners to identify integration challenges and improve the experience of building for mobile. Improve a

About the Team Enterprise Controls & Console is part of Enterprise Engineering. We build the permissions, governance, and administration capabilities that help organizations use and deploy ChatGPT, Codex, and OpenAI products with confidence. We give administrators granular controls over access and security, helping ensure that people and agents operate within the boundaries their organizations define. Our work combines complex backend platform engineering with enterprise product needs and touches every major product and model launch. We build scalable, reusable services and intuitive administration experiences, and provide a shared controls foundation that enables internal teams to introduce new capabilities safely. About the Role We are looking for an experienced backend software engineer to help shape and build the systems behind enterprise access, governance, and sharing. You will bring deep backend expertise and strong product judgment to problems that span multiple OpenAI products, including how people and agents share access and work together. You will lead technical design and delivery, translate ambiguous enterprise needs into clear system behavior, and remain hands-on from implementation through production operation. This role is based in San Francisco. In this role, you will: Design and build backend services for permissions, authorization, and governance across ChatGPT, Codex, and OpenAI APIs. Develop sharing capabilities between people and agents, with clear access rules and enterprise controls that are understandable to administrators and users. Build reusable services and APIs that support workspace administration and console experiences as OpenAI products evolve. Lead architecture and delivery for complex initiatives, aligning product and engineering partners on requirements, tradeoffs, and rollout plans. Translate enterprise needs into clear configuration, predictable permission behavior, and maintainable systems that other product teams can buil