Senior HPC engineer, Research infrastructure

Responsibilities

• In this role, you will work closely with and directly accelerate machine learning researchers, but don't need to be a machine learning expert yourself. 
• We value people who can quickly obtain a deep technical understanding of new domains and enjoy being self-directed and identifying the most important problems to solve. 
• You’ll be managing training HPC clusters at Luma from provisioning to performance tuning.
• Areas of work will include observability, distributed job tracing, GPU diagnostics, software environment management and additional tooling plus work on the actual code to enable necessary features.
• We believe that increasing compute is a huge lever to AI progress. You will have a direct impact on our ability to grow to an unprecedented scale and likewise produce unprecedented results.

Experience

• 8+ years experience as infrastructure engineer or Devops in large and complex distributed systems.
• Deep understanding of networking, bonus points for experience in HPC networking.
• Experience developing high-quality software in a general-purpose programming language, preferably including Python.
• Excellent problem-solving skills and attention to detail.
• Experience with GPUs in large scale clusters is strongly preferred.
• Strong knowledge of observability and monitoring in distributed systems.
• Tenacious at troubleshooting hardware and network topology failures in distributed systemsIndependently driven and able to own problems and build solutions from end-to-end.
• Experience with large scale data center operations, proficiency in cloud orchestration and system tools.
• Please note this role is not meant for recent grads.

Compensation

• In addition to cash base pay, you'll also receive a sizable grant of Luma's equity.
• The pay range for this position is $180000- 220000/yr for Bay Area. Base pay offered will vary depending on job-related knowledge, skills, candidate location, and experience.