Data Client Onboarding Specialist in San Francisco

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

About the Team The Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training. We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings. Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models. About the Role As a Software Engineer on the Frontier Systems team focused on power management, you will work on critical infrastructure to support cutting-edge research. With large-scale supercomputers consuming substantial amounts of power, managing this efficiently is key to maximizing computational capacity. This role is critical to ensuring that our cutting-edge research supercomputing infrastructure runs smoothly, while maintaining reliability and grid-level power stability. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Develop and implement system-level and software-level solutions to optimize power usage in large-scale supercomputers, ensuring efficient and reliable operations. Build automation to monitor power consumption patterns during training workloads and design algorithms to stabilize these fluctuations, preventing issues with grid reliability. Work with researchers and engineers to design tools for real-time monitoring, detection, and remediation of power-related hardware and system faults. Collaborate cross-functionally to translate complex electrical system requirements into code, while driving continuous improvements in power man

The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the Role The Software Engineer, Operating Systems & Orchestration will focus on building systems to manage hardware, configurations, vendors, and the people interacting with our infrastructure. You will design and develop solutions that integrate individual nodes and servers into unified clusters, directly contributing to advancing AI research by streamlining the overall research user experience. 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: Design and build systems to manage both cloud and bare-metal fleets at scale. Develop tools that integrate low-level hardware metrics with high-level job scheduling and cluster management algorithms. Leverage LLMs to coordinate vendor operations and optimize infrastructure workflows. Automate infrastructure processes, reducing repetitive toil and improving system reliability. Collaborate with hardware, infrastructure, and research teams to ensure seamless integration across the stack. Continuously improve tools, automation, processes, and documentation to enhance operational efficiency. You might thrive in this role if you: Have strong software engineering skills with experience in large-scale infrastructure environments. Possess broad knowledge of cluster-level systems (e.g., Kubernetes, CI/CD pipelines, Terraform, cloud providers). Have deep expertise in server-level systems (e.g., systems, containerization, Chef,

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 The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. Make a Difference: Monitor and maintain deployed m

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 Manager, Global Equity Administration to help run our global equity programs 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, and flowcharts current,

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet High Performance Computing (HPC) team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automati

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods. This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact. 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. Responsibilities Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning. Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluati

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet Hardware team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automation to reduce manual work

About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod

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 OpenAI's Hardware organization builds supercompute platforms from silicon and boards to full rack-scale systems to power advanced AI workloads. This role owns end-to-end quality for high-speed interconnect hardware across the product lifecycle: early design influence, supplier/contract manufacturer readiness, qualification, ramp, and fleet quality in lab and data center environments. You will be the quality lead for advanced interconnect components and assemblies, including high-speed copper cables, cable cartridges, patch panels, backplane/cable-backplane solutions, high-speed connectors, and related electro-mechanical interfaces. You will partner closely with electrical, mechanical, SI/PI, systems, reliability, operations, and external vendors to prevent escapes and drive rapid, data-driven containment and corrective action. In this role you will: Own quality for advanced interconnect components and assemblies: high-speed connectors, high-speed copper cables, cable cartridges (e.g., cable cassette style assemblies), patch panels & optics, and backplane/cable-backplane interconnect solutions. Drive quality-by-design: participate in design reviews, DFM/DFx, tolerance stacks, material and plating selections, connector mating strategy, strain relief, and assembly methods to reduce variation and field failures. Define and track quality and reliability metrics (DPPM, yield, escapes, RMA/FRACAS trends, Cpk/Ppk where applicable) for interconnects across NPI and m

About the Team OpenAI’s Platform and Infrastructure Engineering organization advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient technology solutions. Our team builds and maintains robust infrastructure that safeguards OpenAI’s data and systems while ensuring employees are well-equipped and seamlessly connected. By prioritizing security, reliability, and user-centric solutions, we empower OpenAI employees to drive impactful AI research, corporate operations, and product innovation. About the Role As a Software Engineer: Internal Applications, Enterprise, you will build internal products that make technology support and administration safer, faster, and less dependent on manual intervention. You will help reduce reliance on broadly privileged human actions, turn recurring technology problems into paved paths, and build agentic systems that can help resolve tickets end to end. A core part of the role is building the interfaces that bring employees, AI agents, and human responders together in a shared ITSM experience, with the right context, controls, and handoffs at each step. We are seeking engineers who enjoy working across frontend and backend layers on ambiguous, high-leverage enterprise problems. You should bring strong product judgment, solid backend engineering fundamentals, and an interest in building software that changes how technology support, system administration, and agent-assisted operations are delivered. The best fit will care as much about the quality of the operator and employee experience as the correctness of the backend systems behind it. In this role, you will: Build frontend experiences that let employees request help, let agents gather context and take safe actions, and let human responders review, approve, or take over without losing the thread. Reduce reliance on broadly privileged manual actions by replacing them with narrow, auditable, policy-aware aut

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de

About the Team: The OpenAI API team builds the foundation that enables every developer to harness OpenAI’s models safely, reliably, and at scale. We design and operate the systems that power model serving, API access, billing, developer tooling, and enterprise integrations—forming the connective tissue between OpenAI’s research breakthroughs and real-world products. Our mission is to make it effortless for anyone to build with OpenAI technology. We’re responsible for the infrastructure and product layers that allow millions of developers to integrate GPT models, fine-tune behavior, manage data, and deliver transformative experiences to their users. We collaborate across product, research, and engineering teams to ensure that innovation in model capabilities translates directly into value for customers. The API team spans multiple disciplines, including product management, infrastructure engineering, developer experience, and data systems. We care deeply about reliability, scalability, and simplicity—creating tools that let developers focus on their ideas while we handle the complexity of running world-class AI systems. About the Role: We are seeking an experienced Product Manager to define and scale the construction of our data processing, data privacy, billing, and access controls products. You will set strategy and execute on projects like expanding our regional data processing footprint, enabling new inference caching controls in the API or building APIs that make it easier for organizations to manage their spend limits. You will also define the strategy and ship foundational capabilities that ensure customers use OpenAI products securely, privately, and with enterprise-grade controls. This role partners deeply with engineering, security, legal, compliance, finance and leadership to deliver high-trust, enterprise-grade systems. 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 n

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a Software Engineer focused on building and scaling retrieval systems. You’ll work with a team of researchers and engineers to develop infrastructure that enables models to retrieve and act on the right information at the right time. This includes designing and operating indexing systems, retrieval pipelines, and serving layers. This work supports retrieval across OpenAI products and research, with direct impact on system performance, reliability, and scale. Responsibilities Build and scale retrieval infrastructure across indexing, serving, and query execution. Develop low-latency, high-throughput systems for real-time model interaction. Partner with research to productionize embedding and retrieval techniques. Support dense, sparse, and hybrid retrieval pipelines. Own system performance, reliability, and observability at scale. Collaborate across Pretraining, Inference, and Product teams to integrate retrieval end-to-e