About the job
As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale. You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads.
Responsibilities
Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs
Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior
Improve observability, reliability, and performance across OpenAI’s training platform
Debug and resolve issues in complex, high-throughput distributed systems
Collaborate with systems, infrastructure, and research teams to evolve platform capabilities
Extend and adapt failure detection systems or tracing systems to support new training paradigms and workloads
Qualifications
Minimum
Care deeply about performance, stability, and observability in distributed systems
Enjoy finding and fixing issues in large-scale systems and automating operational workflows
Have experience writing low-level software where system details matter
Understand hardware, operating systems, networking, concurrency, and distributed systems
Preferred
Care deeply about performance, stability, and observability in distributed systems
Enjoy finding and fixing issues in large-scale systems and automating operational workflows
Have experience writing low-level software where system details matter
Understand hardware, operating systems, networking, concurrency, and distributed systems
Have a background in high-performance computing or low-level systems engineering
Are excited to work on critical infrastructure that powers frontier AI research