Tpu Kernel Engineer

Anthropic Anthropic · AI Frontier · New York, NY +2 · Remote · AI Research & Engineering

TPU Kernel Engineer responsible for identifying and addressing performance issues across ML systems (research, training, inference), with a focus on designing and optimizing kernels for TPUs. Provides feedback to researchers on model performance impact.

What you'd actually do

  1. Identifying and addressing performance issues across many different ML systems, including research, training, and inference.
  2. Designing and optimizing kernels for the TPU.
  3. Provide feedback to researchers about how model changes impact performance.
  4. Implement low-latency, high-throughput sampling for large language models
  5. Adapt existing models for low-precision inference

Skills

Required

  • ML systems optimization for TPUs, GPUs, or other accelerators
  • low-level optimization
  • large-scale systems problems
  • kernel development
  • performance debugging

Nice to have

  • High performance, large-scale ML systems
  • Designing and implementing kernels for TPUs or other ML accelerators
  • Understanding accelerators at a deep level, e.g. a background in computer architecture
  • ML framework internals
  • Language modeling with transformers
  • pair programming
  • societal impacts of AI

What the JD emphasized

  • performance issues
  • TPU
  • kernels
  • low-level optimization
  • low-latency
  • high-throughput
  • low-precision inference

Other signals

  • TPU optimization
  • kernel development
  • ML systems performance
  • low-level optimization