Training Ml Framework Engineer in San Francisco

About the Team The Codex Research 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 the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measu

About the Team We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale. About the Role We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence. This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI. In this role you will: Improve development workflows for engineers working on model performance infrastructure Design and improve CI/CD, release, validation, and testing pipelines Build and maintain tools that improve reliability, iteration speed, and engineering confidence Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows Contribute to infrastructure efforts that support performance-critical training and inference systems Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure Work in a high-context, ambiguous environment where ownership and good judgment matter You might thrive in this role if: You are motivated by enabling the people around you and helping engineers do their best work You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure You have experience improving large-scale engineering work

About the Team We’re hiring software engineers to make OpenAI’s networking teams more productive. These teams build and operate the high-performance networking systems that support OpenAI’s training and inference infrastructure at frontier scale. About the Role We’re looking for someone who cares deeply about the developer experience of engineers working on complex infrastructure systems — especially around build systems, test architecture, release pipelines, and reliable development workflows. This role will be embedded with OpenAI’s networking team: making it faster, safer, and easier for engineers to build, test, validate, and ship changes across multi-server, networked, and hardware-adjacent environments. In this role you will: Improve development workflows for engineers building and operating OpenAI’s networking systems Design and improve continuous deployment, release, and validation pipelines Build and maintain test harnesses for multi-server, networked, and hardware-backed environments Improve iteration speed across C++, Python, and build-system-heavy codebases Partner with engineers to identify friction in CI, testing, debugging, and deployment workflows Drive testing and reliability strategy for infrastructure components that support large-scale training and inference workloads Work closely with centralized developer experience teams while staying deeply embedded with the networking engineers closest to the systems You might thrive in this role if: You are motivated by helping other engineers move faster and with more confidence You have experience with CI/CD, release pipelines, testing infrastructure, or build systems You are comfortable moving between C++, Python, and build systems such as CMake, Bazel, or Blaze You enjoy building test harnesses, automation, and workflow improvements for complex systems You do not need to be a networking expert, but you are excited to learn enough about the domain to make the team meaningfully more effective When you see

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

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. About the Role The Safety Measurement Product Manager owns OpenAI's approach to measuring harm and safeguard efficacy in production, including driving the strategy for our suite of safety measurement platforms and products used across the company. You will partner closely with our safety research and engineering teams to determine what we measure, where we measure it, and how we measure it, feeding those insights directly into critical leadership decisions and back into our safety work. You will also represent the company's topline safety metric as well as prioritize incoming requests from partner teams to expand our safety measurement platform to more use cases. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Partner closely with data science, research, engineering, policy teams, and other stakeholders to craft a vision for understanding safety outcomes and prevalence on our platforms. Define strategic priorities and product roadmaps focused on improving safety measurement approaches will scaling our measurement platform to more use cases, products, and cross-functional team needs. Establish repeatable processes to integrate cutting-edge AI safety research into OpenAI’s safety m

About the Team The Health team, within OpenAI’s broader Personal AGI organization, has a mission to ensure AGI improves health for all humanity. Improving human health will be one of the defining impacts of AGI. Hundreds of millions of people already turn to ChatGPT for questions about their health and millions of clinicians use it weekly to support care delivery. Increasingly capable models create an opportunity to make high-quality medical intelligence more accessible across patients and clinicians—raising the floor of human health—and accelerate the new capabilities and scientific advances that raise the ceiling of human health. Our job is to make those benefits real. We work across the full model stack—pretraining, midtraining, reinforcement learning, post-training, evaluations, harnessing, and deployment—and connect that research to the patients, clinicians, and real-world outcomes we aim to improve. About the Role We’re looking for an exceptional, hands-on researcher who wants to build frontier health capabilities and turn them into impact at scale. This is a role for someone who can take an important, underdefined problem from 0→1: identify the right bet, build what’s needed to test it, and drive it all the way to a measurable improvement in the models and products we actually ship. We’re especially excited about two kinds of people: researchers with the technical depth to move the frontier in pretraining, reinforcement learning (RL) / post-training, or evals; and researchers with real depth in developing frontier biomedical AI capabilities. Prior experience in healthcare is helpful but not required. Research excellence, velocity, ownership, and alignment with the mission are most important to us. 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 a high-leverage research direction end to end—from deciding which problem matters and h

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE: Are you the person on your team who builds the agent everyone else ends up using? We're looking for an AI Engineer to join our Training Product team and do that at Baseten. You'll build AI-driven product features for the customers training and post-training frontier models on our platform, and you'll raise the ceiling on how Baseten itself uses AI internally, turning manual workflows into agentic ones that make every other team faster. You'll work directly with our research engineers to scope and build products, taking ideas from a research loop that already works internally to something customers can run themselves. This is a hands-on role with real autonomy. You'll pick the problems worth solving, build the harnesses, execution flows, and guardrails that make AI systems reliable, and own the results. If you've been shipping agents and want that to be the job, let's talk. EXAMPLE INITIATIVES: Take a look at these blog posts written by members of our team: Baseten Training: an autoresearch substrate Introducing Baseten Loops Harnesses are everything. Here's how to optimize yours. Building with NVIDIA Nemotron 3 Ultra and LangChain Deep Agents Code on Baseten RESPONSIBILITIES: Build and ship agentic product experiences, including chat-style and assistant-like interfaces, from prototype to GA. Design the harnesses, execution flows, and guardrails that make AI systems reliable in production. Build internal autom

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Being an SDR at Vanta is, first and foremost, about hitting targets and driving revenue. But beyond that, it’s about joining a community that is deeply committed to your success and career growth. We believe that the future of our sales organization lies with our SDRs, which is why we place a strong emphasis on enablement and career advancement. You’ll receive the training, support, and mentorship you need to excel, with a clear path to advance within our sales team. This role is hybrid in office in San Francisco 3 days per week. Vanta is in a period of rapid growth, consistently outpacing our targets while maintaining stellar NPS scores. It’s an incredibly exciting time to join our team. As a Vantan, you’ll be part of a talented group of professionals who are passionate about making an impact. Join us, and you’ll not only help shape the future of internet security but also build a rewarding career in a company that truly values and invests in its people. If this sounds like you, and you're excited to join a growing team, we'd love to hear from you. What you’ll do as a Inbound Sales Development Representative at Vanta : Raise awareness and generate interest for Vanta through cold calling, emails, and social outreach to prospective customers Manage your own book of accounts and set the strategy for effective book management Develop a deep understanding of Vanta’s value proposition and products to effectively communicate their benefits to prospects. Master the use of tools like Salesforce, ZoomInfo, Outreach, LinkedIn Sales Navigator, and 6Sense to identify and prioritize strategic accounts that support our move upmarket. Organiz

What you’ll do Own day-to-day operations for the scanner program and scanner builds in the spa: purchasing/procurement, vendor management, receiving, inventory, and logistics. Stand up lightweight production operations as we move from prototypes to repeatable builds: build planning, kitting, work instructions, and readiness checklists. Partner with Quality to ensure the operational system supports compliance: traceability, document control, training records, NCR/CAPA workflows, and audit readiness. Drive cross-functional execution for the physical spa build-out and scanner integration: schedules, dependencies, risk register, and weekly coordination with vendors and internal teams. Own the “integration glue” across facilities + device ops: commissioning plans, acceptance criteria, and operational handoff (runbooks, maintenance, spares, escalation paths). Build and track operational metrics: cost, budget, lead times, vendor performance, build throughput, and reliability of critical subsystems. Audit of import/export documentation, management of contract renewals, regulatory compliance. What we’re looking for Proven operations leadership in hardware/medical/robotics (or similarly complex electromechanical products), including procurement and vendor management. Strong program management instincts: can run schedules, unblock cross-functional dependencies, and keep priorities clear under ambiguity. Comfort operating in quality/regulatory environments and building processes that are rigorous without slowing a small team. High ownership and bias to action: can jump between spreadsheets, docks, and the lab/site to keep the program moving. Useful experience Experience running prototype-to-production transitions (NPI, EVT/DVT/PVT-style builds, CM/EMS collaboration). Facilities / construction operations experience (GC coordination, MEP commissioning, site readiness). Familiarity with inventory systems and procurement tooling (even “simple but disciplined”).

About the Role We are looking for a senior partner success and learning professional to activate cloud partners to co-sell and deploy customer solutions at scale. This role leads the enablement strategy and execution that equip partner teams to turn joint priorities into measurable customer and business outcomes. As a trusted advisor to strategic partners, you will turn shared business priorities into practical enablement programs that help partner sales, technical, customer success, and leadership teams identify joint opportunities, co-sell effectively, and deploy customer solutions successfully. You will own the partner enablement relationship for an assigned portfolio and work across internal teams to ensure programs are coordinated, scalable, and connected to measurable partner, customer, and business outcomes. This is not a traditional training delivery role or a quota-carrying partner account manager position. It is a consultative, partner-facing role for someone who can shape strategy, build relationships, translate complex AI capabilities into effective learning experiences, lead persuasive enablement sessions, and guide strategic partners toward sustained success. In this role, you will: Own strategic partner enablement and success Serve as the primary enablement and success lead for a portfolio of strategic cloud platforms. Develop a deep understanding of each partner’s business, priorities, audiences, existing learning infrastructure, and strategic relationship with our company. Build partner-specific enablement strategies aligned to shared goals, priorities, and the broader partnership strategy. Establish trusted relationships with partner leaders, alliance teams, enablement stakeholders, sales organizations, technical communities, and post-sales teams. Lead ongoing planning conversations, enablement reviews, stakeholder check-ins, and executive updates that keep partners and internal teams aligned. Identify gaps, risks, opportunities, and emerging partn

About the Team OpenAI is at the center of some of the highest-impact multimodal work in AI. ChatGPT serves a massive global audience, and enables diverse interactions via text, speech, and visuals. As interactive surfaces grow, models also need to adapt to emerging harm, understand user intent and situational context, and respond appropriately. The Chat and Multimodal Safety team is responsible for ensuring that OpenAI’s increasingly multimodal models and products behave safely across these experiences. We develop the research, training methods, and evaluations needed to make these experiences safe. Our work sits at the frontier of responsibly deploying powerful AI, in close partnership with Personal AGI, io, model training, and product teams. About the Role As a Researcher on the Chat and Multimodal Safety team, you will help shape how frontier models perceive and reason the world, and translate that understanding into safe behavior. We’re looking for people who combine deep technical expertise with strong safety judgment. Strong candidates often bridge perception and language: they may have built vision-language models, worked on modality fusion or image encoders, developed multimodal post-training or evaluations, or advanced safety for image, video, or audio 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 new employees. In this role, you will: Define and advance multimodal safety research for text, vision, and audio, connecting perception and semantic understanding to safe model behavior. Build training and evaluation methods for VLMs, including post-training, safety evals, and interventions that help models respond safely and appropriately in varied contexts. Collaborate closely with Personal AGI, Consumer Devices, and product/model teams to translate research into safer ambient, embedded, and personalized multimodal experiences. You might thrive in this role if you:

About the Team The Core Models team helps shape how OpenAI’s frontier models are built, measured, and launched. We work across Research, Engineering, Model Design, Data Science, and Product to turn advances in model capabilities into reliable, useful experiences for people. Our scope includes model planning and launches as well as building data flywheels, evaluations and measurement systems to ensure our models have strong capabilities and behavior. About the Role As a Product Manager for the Core Models team, you'll be at the forefront of defining and guiding the future of how our AI models work in real-world applications. You will connect user needs to model and systems decisions: how prompts are understood; how information is aggregated and made useful for training and evaluation data; and how capabilities move from research prototypes into the mainline model and launch stack. You will operate comfortably across research, infrastructure, and consumer product surfaces, creating clarity where ownership and technical boundaries are still emerging. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Translate user and product goals into clear model requirements, system architecture choices, and research priorities across query understanding, indexing, retrieval, ranking, tool boundaries, data, training, inference, and evaluation. Build closed learning loops that turn product usage, explicit feedback, and other user signals into datasets, evaluations, experiments, training priorities, and launch decisions. Define success across offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost. Partner closely with post-training research, applied product engineering, Model Design, and Data Science to integrate capabilities into the mainline model stack. Create reusable platforms and operatin

About the Team OpenAI’s 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's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside our cloud partners, infrastructure providers, and internal engineering teams, we operate hyperscale AI campuses that support the training and deployment of frontier AI models. The Site Operations team serves as OpenAI's on-site operational presence, helping ensure campuses operate safely, efficiently, and in alignment with Industrial Compute standards. We work closely with Hardware Operations, Infrastructure Delivery, Network Operations, Security, Facilities, Construction, and our infrastructure partners to support day-to-day site execution and maintain operational readiness. As Industrial Compute continues to expand globally, Site Operations plays a critical role in ensuring each campus is prepared to support reliable AI infrastructure at scale. About the Role We are seeking a Site Operations Technician to support the daily operation of Industrial Compute campuses. This role acts as OpenAI's on-site technical representative, helping coordinate activities across hardware operations, facilities, construction, logistics, security, and external service providers. You will perform routine site inspections, support asset tracking, coordinate vendor activities, assist with operational readiness, document site conditions, and help ensure infrastructure issues are identified and resolved quickly. The ideal candidate enjoys working in highly technical environments, is detail-oriented, and thrives in fast-paced operational settings where no two days are the same. Key Responsibilities Perform routine walkthroughs of Industrial Compute facilities to verify operational readiness and identify potential issues. Monitor site conditions and report abnormalities involving hardware spaces, network rooms, utilities, logistics areas, and common infrastructure. Support coordination of vendors, contractors, and partner organizations performing work o

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