Anthropic
Performance Engineer
$280K–$850K
San Francisco, CA +6 · Remote · Full-time · Posted Apr 22, 2024
- Location
- San Francisco, CA
New York City, NY
Seattle, WA
New York, New York, United States
Remote-Friendly US (Travel Required)
San Francisco, California, United States
Seattle, Washington, United States - Experience
- Years of experience required will correlate with the internal job level requirements for the position.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; required field of study is a field relevant to the role as demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not guaranteed for every role and candidate; if an offer is made, Anthropic will make every reasonable effort to obtain a visa.
About the job
Identifies systems bottlenecks in large-scale machine learning and builds systems to improve throughput and robustness.
What you'll do
- Develop systems that optimize throughput and robustness of large distributed systems.
- Implement performance improvements such as high-throughput sampling, GPU kernels, load balancing, and fault-tolerant distributed systems.
- Build quantitative performance models and debug system-level latency issues.
What they ask for
- Significant software engineering or machine learning experience, particularly at supercomputing scale.
- Bachelor’s degree or an equivalent combination of education, training, and/or experience.
- Relevant field of study demonstrated through coursework, training, or professional experience.
Nice to have
- Experience with high-performance, large-scale ML systems, GPU/Accelerator programming, ML framework internals, or OS internals.
- Experience with language modeling using transformers.
Pay
$280,000 — $850,000 USD (base salary)
Tools
ML, GPU/Accelerator, transformers
AI focus
Build and optimize systems for large-scale machine learning, including language-model inference and serving.
Model-written summary · the original posting is authoritative