Systems Generalist, GPT Infrastructure

OpenAI is a leading AI research and deployment company. This role is part of the GPT Infrastructure team, where you will build an automated inference optimization platform that turns research prototypes into scalable, production-ready solutions.

• Design, build, and operate durable APIs and control‑plane services for multi‑hour or multi‑day optimization campaigns, including scheduling, retries, budgets, checkpoints, artifact lineage, and observability.
• Build secure partner‑side runner and grader software that can compile, execute, verify, and benchmark candidate artifacts on third‑party accelerator hardware.
• Integrate hardware profiles, ISA and toolchain context, compilers, runtimes, and inference‑serving engines into a repeatable optimization workflow.
• Turn research prototypes into reliable product surfaces with clear contracts, debuggable failure modes, reproducible outputs, and excellent developer ergonomics.
• Develop correctness and performance evaluation systems spanning latency, throughput, memory use, utilization, and cost efficiency.
• Build artifact, provenance, and qualification workflows that make optimized kernels, binaries, configurations, and reports safe to review and deploy.
• Collaborate with Research, Inference Engineering, Infrastructure, Security, Product, and Strategic Partnerships to deliver production‑ready solutions.
• Drive technical architecture and execution across ambiguous, cross‑functional initiatives that connect OpenAI systems with partner environments.

• 8+ years of professional software engineering experience building large‑scale distributed systems, infrastructure platforms, or cloud services, or equivalent depth of experience.
• Strong programming skills in one or more of C++, Python, Go, or Rust.
• Experience designing and operating highly available backend systems, APIs, job orchestration systems, or durable workflows for production workloads.
• Strong understanding of distributed systems, Linux, networking, storage, containers, and modern cloud architectures.
• Experience debugging complex systems and using measurement, profiling, and benchmarks to guide engineering decisions.
• Proven ability to lead complex technical initiatives as a senior individual contributor and work effectively across organizational boundaries.

• Experience with AI infrastructure, inference‑serving systems, or large‑scale machine learning systems.
• Experience with compilers, runtimes, kernel optimization, or performance engineering; familiarity with technologies such as LLVM, MLIR, Triton, CUDA, or ROCm is a plus.
• Familiarity with GPUs, accelerators, hardware architecture, ISA concepts, or vendor tool chains.
• Experience with inference‑serving frameworks or engines such as vLLM, SGLang, Triton Inference Server, or similar systems.
• Experience building developer platforms, external APIs, remote execution systems, or secure partner‑facing infrastructure.
• Experience working with strategic cloud, hardware, or infrastructure partners.

Compensation Range: $293,000 – $445,000

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 characteristics.