Analytics Lead in United States

About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Revenue team plays a critical role in enabling OpenAI to scale its commercial offerings—overseeing billing operations, deal desk, revenue systems, and revenue accounting. We work cross-functionally with Technical Revenue, Finance Data, and Revenue Systems teams to support complex commercial arrangements, improve operational efficiency, and maintain financial integrity. About the Role As a Revenue Accounting Manager, you will own revenue accounting processes for consumption and usage-based revenue recognition while helping implement and maintain the systems, data flows, and accounting rules that support accurate financial reporting. You will serve as a key execution partner on onboarding new revenue streams, Fusion Accounting Hub rule updates, translating accounting requirements into expected journal entries, source-to-general-ledger mappings, user acceptance testing, data validation, and controlled operating processes. We’re looking for a hands-on revenue accounting owner who combines strong close discipline with systems and data fluency, independently coordinates cross-functional implementation work, and strengthens the accounting infrastructure supporting OpenAI’s growth. 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 the monthly close for usage-based revenue and payment processor accounting, including journal entries, reconciliations, variance analysis, controls, and supporting documentation. Prepare and review revenue-related journal entries while understanding the underlying transaction lifecycle, accounting methodology, billing arrangements, source data, and expected financial reporting outcomes. Perform reconciliations for key revenue accounts, investigate discrepancies, and drive issues to resolution. Own flux

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

About the Team OpenAI is building AI systems that can help professionals perform complex, high-value work with greater speed, rigor, and creativity. Investment banking is one of the most demanding environments for knowledge work: bankers must synthesize fragmented information, exercise judgment under pressure, and produce precise, defensible models, analyses, and client materials. Our team works across Research, Product, Engineering, and Go-to-Market to make OpenAI's models genuinely useful for these workflows. We translate real professional work into product requirements, evaluations, training signals, and repeatable customer solutions. We care not only whether a model can generate an answer, but whether it can deliver accurate, defensible work that experienced bankers can trust and use. 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. About the Role We are looking for a Subject Matter Expert in Investment Banking to help define what excellent AI-assisted banking work looks like and turn that standard into better models and products. You will bring deep, current knowledge of how investment banking work is actually performed, including company and industry research, financial analysis and modeling, valuation, diligence, transaction execution, and the creation and review of client materials. You will use that expertise to design realistic tasks and evaluations, create and assess high-quality reference work, diagnose model failures, and help our technical teams improve model behavior and product experiences. This is a hands-on individual-contributor role for someone who enjoys both doing the work and explaining what makes it good. You should be comfortable moving between an Excel model, a presentation, a source document, an evaluation rubric, a product prototype, and a conversation with researchers or customers. You will help us distinguish outputs that merely look pl

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 We are looking for a highly experienced RTL engineer to own critical on- and off-chip interconnect components for our custom AI accelerator platform. You will drive the microarchitecture and RTL implementation of scalable on-chip communication fabrics connecting high-bandwidth compute, memory, and I/O subsystems as well as purpose-built off-chip interfaces and protocols needed to enable custom computing at scale. This is a senior, hands-on engineering role with broad technical ownership. You will drive design from requirements through the full silicon lifecycle, from architecture definition and performance analysis through RTL implementation, verification closure, physical design convergence, bring-up, and production readiness. You will plan and oversee the work of junior engineers and help drive and develop productive engineering relationships with external partners and help manage partner execution. 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 the microarchitecture, RTL design, and delivery of major SoC interconnect components, including network-on-chip fabrics, switches, routers, bridges, protocol adapters, arbiters, and traffic-management logic as well as off-chip protocol bridges and interfaces. Drive third party engagements to develop novel networking and interface protocols and silicon IP while ensuring high quality and de

About the Team OpenAI’s Financial Engineering and Identity data science team owns how revenue flows through our products and builds the systems that enable people and organizations to access OpenAI products safely, seamlessly, and at global scale. Identity sits at the critical intersection of growth, trust, and user experience. The team owns the experiences and infrastructure behind sign up, sign in, account recovery, authentication, and identity integrations across both consumer and enterprise products. As OpenAI expands across products and markets, Identity plays an increasingly important role in helping more users get started quickly while protecting them from abuse, fraud, and account compromise. About the Role We're looking for the first dedicated Data Scientist to partner with the Identity organization. In this role, you will define how we measure success across the entire identity journey—from first-time sign up and onboarding through authentication, account recovery, and enterprise identity experiences. You'll develop the experimentation frameworks, metrics, and analytical approaches that guide product decisions while helping the team navigate one of Identity's core challenges: optimizing growth while maintaining trust and security. You'll work closely with Product, Engineering, Design, Abuse, Risk, and Go-to-Market teams to identify opportunities, quantify trade-offs, and influence strategy. Some questions can be answered through A/B tests. Others require observational analyses, causal inference, and judgment under uncertainty. This is an opportunity to shape the analytical foundations of a high-impact product area from the ground up. This role is based in San Francisco, CA. We use a hybrid model (3 days/week in office) and offer relocation support. In this role, you will Define the north-star metrics and measurement frameworks used to evaluate the identity experience across consumer and enterprise products. Design and analyze experiments to optimize top-of

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 OpenAI's Human Data Team creates custom data solutions driving groundbreaking research. Our work enhances and evaluates our flagship models and products like ChatGPT, GPT-5, and Sora, and contributes to safety initiatives through collaboration with our Preparedness and Safety Systems teams. About the Role As a Research Program Manager (RPM) in the Human Data team you will partner with research and engineering to design and implement pragmatic solutions for collecting high-quality data. You will be a key interface between our research roadmap, external vendors, AI trainers, and the Human Data engineering team. This role is based in our San Francisco HQ. In this role, you will: Collaborate with Research: Partner with researchers to scope data collection needs, define success metrics, and establish quality measurement frameworks. Design & Execute Data Collection Campaigns: Translate research needs into actionable plans and accelerate execution by leveraging existing tooling and iterating to reach the desired outcome. In many cases, you will need to implement scrappy new solutions while partnering with engineering to design robust/scalable solutions. Unblock Yourself: You must be deeply uncomfortable with the idea of sitting around waiting for external dependencies, and have the technical acumen and drive to figure out how to achieve at least partial success in the interim. Optimize Systems & Processes: Build and optimize dashboards to track campaign performance, leveraging SQL and Python for data analysis and actionable insights. Drive Technical Roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. Scale Your Impact : Advise and empower program managers and vendors to drive day-to-day execution so that you can focus on addressing high priority opportunities. You might thrive in this role if you: Are proficient in SQL and Python for data analysis, including q

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 Power Engineer to characterize, measure, and optimize power consumption across our embedded hardware products. In this role, you will work closely with Electrical Engineering and system software teams to build power test automation, measure subsystem-level power usage, and drive improvements that directly impact battery life, thermal behavior, charging performance, and system reliability. You will help establish the methodologies and metrics used to understand and improve power efficiency across real-world product experiences, from controlled lab environments to representative day-in-the-life usage scenarios. This role requires hands-on experience with embedded hardware platforms, power instrumentation, and the analysis of power profiles and system behavior. 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: Define and develop power testing automation to evaluate system behavior across a range of workloads and operating conditions. Measure subsystem-level power consumption using power breakout probes and other lab instrumentation. Develop and execute power characterization tests spanning basic workloads, complex mixed-use scenarios, and representative day-of-use experiences. Partner closely with Electrical Engineers to identify opportunities to improve system power efficiency. Collaborate with software engineering

About the Team The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf

About the Team OpenAI Finance ensures the organization’s financial integrity and scalability in pursuit of our mission. Our Financial Reporting team is central to delivering accurate, timely, and GAAP-compliant financial information to internal and external stakeholders. We focus on building robust, scalable reporting systems and processes to support rapid organizational growth and complexity. About the Role OpenAI is hiring a Senior Manager, Financial Reporting to help build and run a best-in-class financial reporting engine in a technically complex, rapidly evolving, and high-growth environment. We are looking for a seasoned external reporting professional who pairs strong technical judgment with a roll-up-your-sleeves mindset - owning key reporting deliverables, driving rigorous tie-outs and disclosure quality, and converting ambiguity into audit-ready output. This role will collaborate closely with teams across Accounting, FP&A, Tax, Legal, and Investor Relations to improve reporting processes, streamline data flows, and elevate how financial information is communicated across stakeholders. 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: Modernize reporting workflows through AI integration — Leverage ChatGPT, Codex, and proprietary AI tools to minimize manual effort and accelerate deep analysis, while maintaining the rigorous judgment and accountability required for high-quality, audit-ready outputs. Own end-to-end financial statements and disclosures — Prepare GAAP financial statements, footnotes, and supporting schedules; maintain rollforwards, tie-outs, and internal consistency checks to ensure outputs are complete and audit-ready. Drive audit readiness and execution — Partner with external auditors to manage day-to-day audit workflow (PBC coordination, support quality, issue resolution) and keep reporting on track with minimal 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, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis. 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 will: Design and run experiments that improve agentic model behavior for complex so

About the Team The ChatGPT team works across research, engineering, product, and design to bring OpenAI’s technology to the world. We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, or platform barriers. Our commitment is to facilitate the use of AI to enhance lives, fostered by rigorous insights into how people use our products. About the Role We are looking for an experienced fullstack engineer to join our new ChatGPT Growth team to spearhead high-impact projects that amplify the user base of ChatGPT and Plus Subscribers. Your role will include projects such as optimizing account access, notifications, SEO, fostering value discovery, and virality. As we are in the nascent stages of growth at OpenAI, we will rely on you to discover pivotal areas where strategic bets or incremental efforts can catalyze significant impact. We value engineers who are impact-driven, autonomous, adept at discerning crucial insights from experimental results, and have a strong intuition for how to remove barriers to unlocking the magic of ChatGPT. In this role, you will: Drive long-term growth of ChatGPT through a combination of data analysis, product ideation, and experimentation to optimize product experiences. Plan and deploy backend APIs necessary to power these product experiences. Execute on projects by working closely with research, product, design, data science and other members of product teams to land impact on product goals. Create a diverse and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group-think. You might thrive in this role if you: Shipped features on web that optimize the user funnel, such as landing pages, product pages, purchase flows, search flows, etc. Are highly analytical and have experience designing and implementing A/B te

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 You will develop and evolve the tooling ecosystem that hardware engineers rely on every day — from hardware compilers and IR transformations to simulation, debugging, and automation infrastructure. The work spans software engineering, compiler concepts, and practical hardware workflows, with direct impact on how quickly and effectively we design next-generation AI systems. You’ll collaborate closely with architects, RTL designers, and verification engineers to translate real engineering friction into durable, scalable tooling solutions. In this role you will: Build and improve the software tooling that makes hardware teams faster: compilation, IR transforms, RTL generation, simulation, debug, and automation. Extend and integrate hardware compiler stacks (frontends, IR passes, lowering, scheduling, codegen to Verilog/SystemVerilog) and connect them to real design workflows. Improve developer experience and reliability: reproducible builds, better error messages, faster iteration loops, and dependable CI and regression infrastructure. Work closely with designers and verification engineers to turn real pain points into durable tools. Dive into RTL when needed: read and reason about Verilog/SystemVerilog to debug issues, validate tool output, and improve debuggability. Be willing to go all the way down the stack when necessary, including gate-level views, synthesis results, and implementation artifacts. Help enable PPA optimization loops by building analysis and au

About the Role The Engineering Acceleration team builds and operates the foundational systems that engineers use to build, test, and ship ChatGPT, the API, and OpenAI's infrastructure. We are looking for an engineer to help evolve OpenAI's build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, and software quality. You will work on the systems that determine how quickly and confidently engineers can move: Bazel-based builds, Buildkite pipelines, test selection, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to make OpenAI one of the most productive engineering organizations in the world while preserving a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping useful systems instead of fighting infrastructure. In This Role, You Will Own and evolve Bazel-based build and test workflows across a large, polyglot monorepo. Design and maintain Starlark rules, macros, toolchains, and integrations that make builds reproducible, hermetic, and easy for product teams to adopt. Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, test sharding, retry behavior, and flake isolation. Build systems that reduce unnecessary CI work through affected-target detection, dependency graph analysis, test selection, caching, batching, and smarter scheduling. Improve local development workflows so engineers can reproduce CI behavior, debug build failures, and iterate quickly without learning every detail of the build stack. Operate and optimize build infrastructure across Docker/OCI images, Kubernetes-based runners, cloud resources, and remote cache/exec

About the Team The Software Engineering Firmware team builds reliable, high-performance systems on custom hardware. We work closely with hardware engineers to design, optimize, and ship software that bridges cutting-edge devices and real-world constraints like memory, power, and latency. Our work spans early prototyping through product launch, ensuring that our embedded platforms are robust, efficient, and production-ready. About the Role As a Firmware Engineer , you will design, implement, and debug software for embedded devices. You’ll own low-level bring-up, write production C/C++ code, and partner closely with hardware teams to deliver reliable, high-performance systems. We’re looking for engineers with deep embedded expertise, strong debugging skills, and a passion for building systems that perform under real-world conditions. This role is based in San Francisco, CA . We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement, and debug software for embedded devices. Contribute to defining software requirements, interfaces, and test plans. Bring up and debug new boards. Analyze performance, memory, and power profiles and implement optimizations. Investigate field issues, perform root-cause analysis, and deliver robust fixes. Foster good software engineering practices. You might thrive in this role if you: Have deep experience shipping embedded systems (around 10+ years). Are proficient in C and C++. Are familiar with embedded toolchains, operating systems, and debugging tools. Have experience with both rapid prototyping and scalable product development. (Nice to have) Have experience with Zephyr RTOS. (Nice to have) Have worked with networking/wireless stacks (BLE, Wi-Fi). (Nice to have) Have experience with robotic system bring-up or Linux kernel development. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose arti