Performance Engineer

Overview

As a Performance Engineer, you will solve large-scale ML systems problems and build systems that optimize throughput and robustness for distributed systems.

What you'll do

• Identify novel systems problems that arise when running ML algorithms at scale.
• Develop systems to optimize throughput of large distributed systems.
• Improve robustness of distributed systems used for ML workloads.
• Work on large-scale systems problems with a focus on performance.
• Participate in pair programming.
• Design and implement performance and reliability improvements for production-like workloads.

What you'll need

• Significant software engineering or machine learning experience, particularly at supercomputing scale.
• Results-oriented approach with a bias towards flexibility and impact.
• Ability to take on tasks beyond the job description.
• Comfort with pair programming.
• Interest in learning more about machine learning research.

Nice to have

• Experience with high performance, large-scale ML systems.
• Experience with GPU/accelerator programming.
• Experience with ML framework internals.
• Experience with OS/kernel internals.
• Experience with language modeling with transformers.

Details

• Annual salary range: $280,000–$850,000 USD.
• Location-based hybrid policy: expected to be in an office at least 25% of the time.
• Visa sponsorship is available, with variability by role/candidate.