Software Engineer, Hardware Health Specialist

4 weeks ago


San Francisco, California, United States OpenAI Full time

About the Team

At OpenAI, our Hardware Health team is dedicated to ensuring the optimal performance and reliability of our custom-built hyperscale supercomputers. We focus on maximizing supercomputing capacity for research and ensuring that our researchers are minimally impacted by hardware faults.

The Hardware Health team operates within the broader Platform organization, which is incubated inside OpenAI's Research team. Our work is on the front lines of innovation, supporting the engineering and research required to train large-scale AI models of unprecedented capability.

About the Role

As a software engineer on Hardware Health, you will work to maintain a sophisticated and comprehensive suite of hardware health tests and collaborate with researchers and our Supercomputing team on root-causing and reliably reproducing newly discovered problems. Prior hardware expertise is not required for this role.

The team moves at a fast pace and provides individuals with a high degree of autonomy and a strong ability to affect change.

An ideal candidate would have:

  • 7+ years of industry experience in software engineering
  • A balance of building and operational skills
  • Excellent abilities developing in Python and shell scripting
  • A high degree of comfort digging into noisy data with SQL, PromQL, and Pandas
  • Experience developing reproducible analyses/building dashboards and visualizations
  • Proven track record in attention to detail, with examples of identifying and rectifying data anomalies
  • A strong sense of ownership causing them to very carefully monitor outcome of deployed updates
  • Prior TL experience (2+ years) as this is a 0-1 effort with team growth on the horizon

Bonus Points if you have expertise and interest in low-level details of hardware components, protocols, and associated Linux tooling (e.g., PCIe, Infiniband, networking, power management, kernel perf tuning) or visualization of large data centers and networks.


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