Software Engineer, GPU Infrastructure- ChatGPT Engineering

ChatGPT Engineering builds and operates the compute platform powering one of the world's largest AI products. Every ChatGPT conversation relies on massive GPU clusters serving inference workloads with high reliability, efficiency, and performance.

As our GPU fleet continues to grow, we're investing in the infrastructure that operates it. Our team builds the tooling, automation, and intelligent systems that make GPU infrastructure scalable, observable, and increasingly autonomous. We work across production engineering, distributed systems, capacity management, and AI-powered operational tooling to help researchers and product teams move faster while maximizing the efficiency of every GPU.

This is a unique opportunity to work on infrastructure at the frontier of AI, where small improvements in fleet efficiency, reliability, and automation have an outsized impact on the development and deployment of AGI.

We're looking for a Software Engineer with deep experience operating large-scale GPU or compute infrastructure.

You'll design and build the systems that manage GPU clusters at scale-from fleet health and capacity planning to operational automation and intelligent agents that reduce manual intervention. You'll partner closely with infrastructure, research, and product engineering teams to improve reliability, developer productivity, and overall compute utilization.

This role is ideal for engineers who enjoy solving complex operational challenges, building internal platforms, and working on infrastructure that directly powers frontier AI.

• Design, build, and operate software that manages large-scale GPU infrastructure supporting ChatGPT inference.
• Build internal platforms, tooling, and AI-powered agents that automate fleet operations and reduce operational overhead.
• Improve observability, reliability, and operational efficiency across thousands of GPUs.
• Develop systems for capacity planning, scheduling, fleet health monitoring, and incident response.
• Identify infrastructure bottlenecks and implement solutions that improve utilization, scalability, and performance.
• Partner closely with research, platform, networking, and systems teams to continuously improve our compute platform.
• Help establish engineering best practices around operational excellence, automation, and infrastructure reliability.

• Have experience operating large-scale production infrastructure, preferably GPU clusters or other compute-intensive distributed systems.
• Have a background in Production Engineering, Site Reliability Engineering (SRE), Infrastructure Engineering, or Platform Engineering.
• Have built software that automates operational workflows rather than relying on manual processes.
• Have experience with Kubernetes, Linux systems, container orchestration, or distributed infrastructure.
• Understand infrastructure observability, monitoring, capacity planning, and incident management.
• Enjoy identifying cross-team pain points and building reusable platforms that improve developer productivity.
• Are comfortable working across software engineering and systems operations, owning problems end-to-end.
• Thrive in fast-moving environments with significant technical ambiguity.

• 5+ years of software engineering experience building production infrastructure.
• Strong programming skills in Go, Python, C++, Rust, or similar systems languages.
• Experience designing and operating highly available distributed systems.
• Experience with GPU infrastructure, high-performance computing, ML infrastructure, or large-scale compute platforms.
• Experience with Kubernetes, cloud infrastructure, Linux, networking, and observability tooling.
• Excellent debugging, systems design, and operational problem-solving skills.
• Strong communication skills and experience collaborating across engineering organizations.

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.

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.

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