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If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p><strong>About the team</strong></p>\n<p>OpenAI’s Forward Deployed Engineering (FDE) org sits at the intersection of product, engineering, research, and go-to-market. We take frontier platform capabilities into the real world with design partners, turning raw customer signal into shipped software, repeatable patterns, and durable products.</p>\n<p><strong>About the role</strong></p>\n<p>Platform Engineer is a role within Forward Deployed Engineering (FDE) for strong software and ML engineers who want to build new platform capabilities from scratch, grounded in real customer deployments.</p>\n<p>You will partner with customer-tagged FDEs who are driving delivery and customer outcomes, and embed where you can provide the highest leverage. In practice that means working in the trenches on architecture, product shaping, refactoring, hardening, and reusable abstractions, while preserving the pod’s ownership of customer understanding and day-to-day execution. You will also collaborate closely with our B2B Platform Team and other long-term owners to align early on what should generalize, what should remain customer-specific, and what “ready for handoff” looks like.</p>\n<p><strong>This role does not require travel. It is based in San Francisco or New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel is optional-by-project and typically &lt;0%, with occasional spikes for key embeds or launches.</strong></p>\n<p><strong>In this role you will</strong></p>\n<ul>\n<li><strong>Provide hands-on leverage to customer pods:</strong> embed with customer-tagged FDE teams to support generalization, contributing directly in architecture, product shaping, refactoring, and implementation.</li>\n</ul>\n<ul>\n<li><strong>Turn repeated signals into platform bets:</strong> translate cross-customer patterns into crisp hypotheses with clear success criteria, scope, and a validation plan that fits real account constraints.</li>\n</ul>\n<ul>\n<li><strong>Raise the engineering bar through tooling and mentorship:</strong> set org-wide quality norms through high-signal code review and pairing, and build lightweight developer tooling that makes good architecture, readability, and correctness the default across FDE.</li>\n</ul>\n<ul>\n<li><strong>Collaborate as part of cross-functional platform teams:</strong> partner closely with B2B Product, customer-tagged FDEs, ops, and business partners to bring the right products and platform capabilities to market.</li>\n</ul>\n<ul>\n<li><strong>Lead complex platform capabilities end-to-end when needed:</strong> for high-leverage primitives like our Context Platform, act as DRI from requirements through implementation, make key tradeoffs explicit, and pull in customer pods early to keep the work grounded in real deployments.</li>\n</ul>\n<p><strong>You might thrive in this role if you</strong></p>\n<ul>\n<li>Bring <strong>5+ years of software engineering or ML engineering experience</strong> with a track record of <strong>shipping 0→1 capabilities</strong> that other engineers or customers depend on. Experience in high-ambiguity, fast-iteration environments (startups or product-centric teams) is a plus.</li>\n</ul>\n<ul>\n<li>Have owned <strong>customer-adjacent technical work</strong> end-to-end, from scoping and hypothesis-setting through production adoption, and improved outcomes through structured iteration (instrumentation, evals, error analysis, and tightening success criteria over time).</li>\n</ul>\n<ul>\n<li>Have built or operated systems where <strong>reliability, security, and governance</strong> materially shaped design (permissions/RBAC, auditability, data access boundaries, rollout safety, observability, and incident-driven hardening).</li>\n</ul>\n<ul>\n<li>Communicate clearly across <strong>engineering, product, go-to-market, and executive audiences</strong>, simplifying complex ideas and translating technical tradeoffs into adoption impact, sequencing decisions, and measurable outcomes. You can credibly “pitch” a platform bet in a customer conversation.</li>\n</ul>\n<ul>\n<li>Default to systems thinking: you turn ambiguous feedback, failures, and escalations into durable <strong>product requirements and reusable platform capabilities</strong>, not one-off fixes or bespoke delivery work.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p><strong>Experience</strong></p>\n<p>5+ years of software engineering or ML engineering experience</p>\n<p><strong>Employment Type</strong></p>\n<p>Full-time</p>\n<p><strong>Workplace Type</strong></p>\n<p>Hybrid</p>\n<p><strong>Category</strong></p>\n<p>Engineering</p>\n<p><strong>Industry</strong></p>\n<p>Technology</p>\n<p><strong>Salary Range</strong></p>\n<p>$230K – $385K</p>\n<p><strong>Required Skills</strong></p>\n<ul>\n<li>Software engineering</li>\n<li>ML engineering</li>\n<li>Architecture</li>\n<li>Product shaping</li>\n<li>Refactoring</li>\n<li>Hardening</li>\n<li>Reusable abstractions</li>\n<li>Systems thinking</li>\n</ul>\n<p><strong>Preferred Skills</strong></p>\n<ul>\n<li>Experience in high-ambiguity, fast-iteration environments</li>\n<li>Customer-adjacent technical work</li>\n<li>Reliability, security, and governance</li>\n<li>Communication across engineering, product, go-to-market, and executive audiences</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b83a3282-d15","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/059ac93e-3fc9-42e9-a4f4-367c0fd5de14","x-work-arrangement":"Hybrid","x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$230K – $385K","x-skills-required":["Software engineering","ML engineering","Architecture","Product shaping","Refactoring","Hardening","Reusable abstractions","Systems thinking"],"x-skills-preferred":["Experience in high-ambiguity, fast-iteration environments","Customer-adjacent technical work","Reliability, security, and governance","Communication across engineering, product, go-to-market, and executive audiences"],"datePosted":"2026-03-08T22:16:37.130Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Software engineering, ML engineering, Architecture, Product shaping, Refactoring, Hardening, Reusable abstractions, Systems thinking, Experience in high-ambiguity, fast-iteration environments, Customer-adjacent technical work, Reliability, security, and governance, Communication across engineering, product, go-to-market, and executive audiences","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":230000,"maxValue":385000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_32b83135-974"},"title":"Software Engineer, Data Infrastructure - Research","description":"<p><strong>Software Engineer, Data Infrastructure - Research</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Scaling</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$250K – $380K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong><strong>About the Team</strong></strong></p>\n<p>The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life.</p>\n<p><strong><strong>About the Role</strong></strong></p>\n<p>We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume.</p>\n<p><strong><strong>In this role, you will:</strong></strong></p>\n<ul>\n<li>Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory.</li>\n</ul>\n<ul>\n<li>Build proactive testing and scale validation pipelines for dataset loading at GPU scale.</li>\n</ul>\n<ul>\n<li>Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience.</li>\n</ul>\n<ul>\n<li>Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt.</li>\n</ul>\n<ul>\n<li>Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized.</li>\n</ul>\n<ul>\n<li>Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training).</li>\n</ul>\n<ul>\n<li>Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets.</li>\n</ul>\n<p><strong><strong>You might thrive in this role if you:</strong></strong></p>\n<ul>\n<li>Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.</li>\n</ul>\n<ul>\n<li>Have experience building APIs, modular code, and scalable abstractions, while recognizing that abstractions ultimately serve the users and UX is an important part of the abstractions design.</li>\n</ul>\n<ul>\n<li>Are comfortable debugging bottlenecks across large fleets of machines.</li>\n</ul>\n<ul>\n<li>Take pride in building infrastructure that “just works,” and find joy in being the guardian of reliability and scale.</li>\n</ul>\n<ul>\n<li>Are collaborative, humble, and excited to own a foundational (if not glamorous) part of the ML stack.</li>\n</ul>\n<p><strong>Bonus points if you:</strong></p>\n<ul>\n<li>Have background knowledge in data math, probability, or distributed data theory.</li>\n</ul>\n<ul>\n<li>Have worked with GPU-scale distributed systems or dataset scaling for real-time data</li>\n</ul>\n<p><strong><strong>About OpenAI</strong></strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_32b83135-974","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/b7a2e30f-c5f6-4710-b53e-64d64bcce189","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$250K – $380K • Offers Equity","x-skills-required":["distributed systems","data pipelines","infrastructure","APIs","modular code","scalable abstractions","data math","probability","distributed data theory","GPU-scale distributed systems","dataset scaling"],"x-skills-preferred":["collaborative","humble","excited to own a foundational part of the ML stack"],"datePosted":"2026-03-06T18:30:12.517Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"distributed systems, data pipelines, infrastructure, APIs, modular code, scalable abstractions, data math, probability, distributed data theory, GPU-scale distributed systems, dataset scaling, collaborative, humble, excited to own a foundational part of the ML stack","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":250000,"maxValue":380000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c7be42f1-99f"},"title":"Software Engineer, Cloud Infrastructure","description":"<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Applied AI</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$230K – $490K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses.</p>\n<p>You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more.</p>\n<p>We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth.</p>\n<p><strong>About the Role</strong></p>\n<p>The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably.</p>\n<p>This role is based in San Francisco, CA.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Design and build the development and production platforms that power our products, enabling reliability and security at scale</li>\n</ul>\n<ul>\n<li>Ensure our infrastructure can scale to the next order of magnitude</li>\n</ul>\n<ul>\n<li>Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think</li>\n</ul>\n<ul>\n<li>Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have 5+ years building core infrastructure</li>\n</ul>\n<ul>\n<li>Have experience operating orchestration systems such as Kubernetes at scale</li>\n</ul>\n<ul>\n<li>Have experience building abstractions over cloud platforms</li>\n</ul>\n<ul>\n<li>Take pride in building and operating scalable, reliable, secure systems</li>\n</ul>\n<ul>\n<li>Are comfortable with ambiguity and rapid change</li>\n</ul>\n<p>This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees.</p>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. 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