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OpenAI

Host Systems Software Engineer

San Francisco (Remote)$266k–$445kfulltimemidAdded 1 month ago

About this role

OpenAI seeks a systems software engineer to design and build host-side software for custom AI infrastructure, focusing on kernel drivers, high-performance I/O, and networking. You'll work across hardware and software boundaries to optimize and bring up next-generation AI systems from low-level interfaces through production deployment.

What you'll do

  • Design and implement Linux kernel drivers and userspace components for AI infrastructure
  • Optimize software for high-throughput, low-latency communication including RDMA and networking
  • Develop software for PCIe, DMA, network interfaces, and accelerator device interaction
  • Bring up new hardware platforms and diagnose cross-layer issues in kernel, firmware, and hardware
  • Build tooling for integration, testing, diagnostics, and performance characterization
  • Collaborate with hardware, networking, and external vendor teams on platform integration

What they're looking for

  • C/C++ programming
  • Linux kernel development and systems fundamentals
  • RDMA, RoCE, and kernel networking
  • PCIe, DMA, and I/O subsystem knowledge
  • Hardware platform bring-up and debugging
  • Python and Linux automation tooling
  • Performance optimization and profiling
  • Rust (preferred)
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OpenAI

OpenAI builds AI infrastructure and products, including large-scale data center campuses for AI computing and generative AI applications for enterprise customers. The company is hiring civil engineers, project engineers, electrical design engineers, data center R&D engineers, and AI deployment engineers to expand its infrastructure capabilities and help customers deploy AI solutions.

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Likely interview questions

  • Walk us through your experience developing Linux kernel drivers. What was the most complex driver you've built, and how did you debug issues across hardware and software boundaries?
  • Describe your hands-on experience with RDMA, PCIe, or DMA. How have you optimized high-throughput, low-latency communication paths in production systems?
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