Reliability Engineer, Supercomputing

Job summary

Responsibilities

We're hiring an engineer to ensure the reliability of our GPU supercomputing fleet, owning the seam between hardware, firmware, and operating system. You will track the long tail of hardware issues: We are conducting frontier research in AI and a single bad NIC, HBM or a kernel driver edge case…

• Investigate, reproduce, and remediate issues across large GPU clusters.
• Own the drivers, kernel surface, and diagnostics that span hardware, firmware, and OS.
• Automate the monitoring of fleet reliability and analyze error rates to validate whether a fix or firmware change measurably reduced failures rather than shifting them around.
• Drive the firmware lifecycle: tracking, qualification, staged rollout, and regression analysis.
• Engage vendors directly — GPUs, server OEMs, NIC vendors, and storage vendors — to get real fixes rather than ticket numbers. Manage RMA flows when hardware needs to come out.

What they're looking for

• Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
• Proficiency in at least one backend language (we use Python or Rust).
• Experience operating large‑scale clusters and container orchestration systems (e.g. Kubernetes or Slurm).
• Comfort operating across the stack and owning projects end-to-end.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.

Tech stack

• Python
• Rust
• Kubernetes