Thinking Machines Lab
Reliability Engineer, Supercomputing
$350K–$475K
San Francisco · On-site · Full-time · Posted Jun 24, 2026
- Education
- Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
- Visa sponsorship
- Visa sponsorship is available; the company cannot guarantee success for every candidate or role.
About the job
Ensures reliability of the GPU supercomputing fleet by diagnosing hardware, firmware, driver, and operating-system issues and driving fixes with internal teams and vendors.
What you'll do
- Investigate and remediate issues across large GPU clusters; identify root causes spanning hardware, firmware, and the OS.
- Automate fleet reliability monitoring, analyze error rates, and manage firmware qualification, rollout, and regression analysis.
- Coordinate fixes and RMA flows with hardware vendors, and write postmortems and vendor cases.
What they ask for
- Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
- Proficiency in at least one backend language (Python or Rust).
- Experience operating large-scale clusters and container orchestration systems, such as Kubernetes or Slurm.
- Comfort operating across the stack and owning projects end-to-end.
Nice to have
- Fluency with Linux systems and debugging tools; Linux kernel literacy.
- Experience analyzing reliability statistically, tracing application symptoms to hardware root causes, or engaging hardware vendors directly.
Pay
$350,000 - $475,000 USD (base salary)
Tools
Python, Rust, Kubernetes, Slurm, Linux, BMC, iDRAC, IPMI
AI focus
Supports reliability of the GPU fleet used for frontier AI research; no direct AI development work is specified.
Model-written summary · the original posting is authoritative