Performance Engineer

3 weeks ago


San Francisco CA, United States Anthropic Limited Full time

Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you'll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also.

You may be a good fit if you:
  • Have significant software engineering or machine learning experience, particularly at supercomputing scale
  • Are results-oriented, with a bias towards flexibility and impact
  • Pick up slack, even if it goes outside your job description
  • Enjoy pair programming (we love to pair)
  • Want to learn more about machine learning research
  • Care about the societal impacts of your work
Strong candidates may also have experience with:
  • High performance, large-scale ML systems
  • GPU/Accelerator programming
  • ML framework internals
  • OS internals
  • Language modeling with transformers
Representative projects:
  • Implement low-latency high-throughput sampling for large language models
  • Implement GPU kernels to adapt our models to low-precision inference
  • Write a custom load-balancing algorithm to optimize serving efficiency
  • Build quantitative models of system performance
  • Design and implement a fault-tolerant distributed system running with a complex network topology
  • Debug kernel-level network latency spikes in a containerized environment

Deadline to apply: None. Applications will be reviewed on a rolling basis.

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