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OpenAI

Full Stack Engineer, Fleet Scheduling

Hybrid · San Francisco, CA

This hybrid role accepts applicants from: United States.

Apply on the employer's siteOriginal listingJSON

PeopleSeek Talent does not submit applications. The button opens the employer's own page; this listing was verified 4 hours ago.

PayUSD 230,000 – 490,000 per year
Work arrangementHybrid
Who can applyPeople in United States
LevelNot stated
TypeFull time
Occupationmine shift manager
LanguageNot stated
Posted6 February 2025
Last verified4 hours ago
StatusActive

About the role

About the Team
Full Stack engineers within the Fleet Scheduling team are dedicated to building intuitive and scalable interfaces that empower researchers to efficiently manage AI workloads across some of the largest supercomputers in the world. Our focus is on developing robust, high-performance systems that provide real-time insights, resource tracking, and seamless interaction with complex infrastructure. We aim to optimize resource allocation, minimize operational overhead, and create user-friendly tools that enhance researcher productivity and system transparency.

About the Role
You will design, develop, and operate web-based systems that provide a powerful and intuitive interface to OpenAI’s supercomputing clusters. You will collaborate closely with researcher, product and infrastructure teams to deliver scalable solutions that enable seamless monitoring, job scheduling, and resource management. This is an opportunity to work at the cutting edge of AI infrastructure, designing tools that scale to exascale workloads while maintaining usability and performance.

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 develop full-stack web applications to track, monitor, and manage large-scale AI workloads in real time.

  • Collaborate with researchers and infrastructure teams to translate complex operational needs into intuitive UIs and scalable backends.

  • Build data visualization tools (e.g., Gantt charts, dashboards) to provide insights into job scheduling and resource allocation.

  • Optimize backend services to handle massive data throughput while ensuring low-latency performance and high availability.

  • Implement frontend components that provide seamless interactions with scheduling, storage, and compute systems.

  • Ensure system security, reliability, and scalability across globally distributed supercomputing infrastructure.

You might thrive in this role if you:

  • Significant experience in full-stack development, with expertise in modern frontend frameworks (React, Vue, or Angular) and backend technologies (Python, Go, or Node.js).

  • Experienced in building scalable, high-performance web applications for complex distributed systems.

  • Strong understanding of RESTful and GraphQL APIs, distributed databases, and cloud infrastructure (especially Azure).

  • Execution-focused with a keen eye for usability, performance, and scalability in enterprise-scale systems.

  • Comfortable working in fast-paced, highly collaborative environments with tight timelines and evolving priorities.

Bonus points if you:

  • Have experience working with Kubernetes, Docker, and cloud-native application deployment.

  • Understand AI/ML workload scheduling and orchestration challenges.

  • Have experience with real-time data processing, visualization libraries, and observability tooling.

About OpenAI

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. 

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

Listed via OpenAI · first seen 22 October 2026 · last verified 27 October 2026

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