Description
Compensation
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.
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- 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)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 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)
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
About the Team
The Frontier Clusters team at OpenAI builds, launches, and supports the largest supercomputers in the world!
Our mission is to make them work for frontier model training. We bring new clusters online, scale them to larger and larger training runs, improve cluster availability, and work with researchers to understand and fix the issues that keep jobs from running reliably.
About the Role
You will build web-based tools that help answer critical questions about our supercomputing clusters: Why is this training job down? What is preventing these nodes from being ready? Where are we losing usable capacity, and what should we fix first? How can agents help us solve this problem?
You will work closely with researchers and infrastructure teams to identify the highest-leverage problems in cluster operations, then design and build solutions. That could mean improving cluster availability, giving users and operators better insight into job failures and performance, or building workflows that make scheduling, debugging, and resource management more effective at massive scale.
In this role, you will:
- Build full-stack web applications that help researchers and operators understand cluster health, job failures, and usable capacity in real time.
- Turn questions like “why is this job down?” and “what is preventing these nodes from being ready?” into clear, actionable product experiences.
- Collaborate closely with researchers and infrastructure teams to identify high-leverage operational problems and build tools that solve them.
- Design data models, APIs, and visualizations that make large-scale scheduling, resource allocation, and cluster behavior easier to inspect and reason about.
- Develop scalable backend services that process high-volume cluster and workload data with low latency and high reliability.
- Build intuitive frontend workflows that connect users to the underlying scheduling, storage, and compute systems.
- Raise the bar for reliability, performance, and security in the systems used to operate OpenAI’s frontier compute.
You might thrive in this role if you:
- Have significant experience in full-stack development, with expertise in modern frontend frameworks such as React, Vue, or Angular, and backend technologies such as Python, Go, or Node.js.
- Have built scalable, high-performance web applications for complex distributed systems.
- Understand APIs, distributed data systems, and cloud infrastructure.
- Are execution-focused, with a strong eye for usability, performance, and scalability.
- Are 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.
Compensation Range:
$230K – $347K USD