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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>Job Description</strong></p>\n<p>This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from</p>\n<ul>\n<li>Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems</li>\n</ul>\n<ul>\n<li>Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades</li>\n</ul>\n<ul>\n<li>Supporting research workflows with service frameworks and deployment systems</li>\n</ul>\n<ul>\n<li>Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching</li>\n</ul>\n<ul>\n<li>Much more!</li>\n</ul>\n<p><strong>About the Role</strong></p>\n<p>As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI&#39;s mission to advance AI capabilities responsibly.</p>\n<p>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.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems.</li>\n</ul>\n<ul>\n<li>Interface with researchers and product teams to understand workload requirements</li>\n</ul>\n<ul>\n<li>Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have experience with hyperscale compute systems</li>\n</ul>\n<ul>\n<li>Possess strong programming skills</li>\n</ul>\n<ul>\n<li>Have experience working in public clouds (especially Azure)</li>\n</ul>\n<ul>\n<li>Have experience working in Kubernetes</li>\n</ul>\n<ul>\n<li>Execution focused mentality paired with a rigorous focus on user requirements</li>\n</ul>\n<ul>\n<li>As a bonus, have an understanding of AI/ML workloads</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. 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Scalability, reliability, security, and usability are the core concerns of the team.</p>\n<p><strong>About the Role</strong></p>\n<p>As an engineer on the Storage Infrastructure team, you will design, build, and operate Exascale systems to scalably and reliably manage our research data across multiple regions.</p>\n<p>We’re looking for distributed systems engineers who have worked on exascale data management systems or distributed filesystems.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Develop software to manage exascale data, and make it accessible to researchers</li>\n</ul>\n<ul>\n<li>Drive the reliability, predictability, and cost effectiveness of our storage systems</li>\n</ul>\n<ul>\n<li>Interface with researchers to understand and accommodate data use-cases</li>\n</ul>\n<ul>\n<li>Ensure the security of our critical datasets</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have a deep understanding of distributed systems principles and a proven track record in designing and building scalable, reliable, and secure storage solutions.</li>\n</ul>\n<ul>\n<li>Possess strong programming skills</li>\n</ul>\n<ul>\n<li>Have experience working in public clouds (especially Azure)</li>\n</ul>\n<ul>\n<li>Are familiar with AI/ML data access patterns</li>\n</ul>\n<ul>\n<li>Bias for action and comfort building in a fast paced, dynamic environment</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. 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