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Software Engineer, Platform Systems

OpenAI

Software Engineer, Platform Systems is a still-open role at OpenAI on Jobrow. Location: On-site · San Francisco · California · United States. Listed pay: $380k–$500k. Sourced from the company's public Ashby board. First seen 2 months ago; last confirmed 9 days ago. Apply on the employer ATS — Jobrow is not the employer.

Pay
$380k–$500k
Workplace
On-site
Location
San Francisco · California · United States
First seen
2 months ago
Last seen
9 days ago
Board
Ashby
Apply

About this role

ABOUT THE TEAM The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems.

  • Function: Infrastructure
  • Seniority: mid

Location & pay

On-site · San Francisco · California · United States Listed pay on Jobrow: $380k–$500k.

Source

Jobrow reads the public Ashby board for OpenAI. First seen 2 months ago; last seen 9 days ago. We are not the employer — apply only on the company ATS.

Posting

ABOUT THE TEAM The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers. Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale. We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform. ABOUT THE ROLE 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. This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging. IN THIS ROLE, YOU WILL - 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 YOU MIGHT THRIVE IN THIS ROLE IF YOU - 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 syst

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