Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The TPU Kernel Engineer will identify and address performance issues across various machine‑learning systems, design and optimize TPU kernels, provide feedback to researchers on model changes, and solve large‑scale systems problems and low‑level optimization.
TPU Kernel Engineer at Anthropic
Hybrid - San Francisco, CA, USA
More jobs at AnthropicSalary
USD 280,000 - 850,000
Requirements
Skills
- Significant experience optimizing ML systems for TPUs, GPUs, or other accelerators
- Results-oriented with a bias towards flexibility and impact
- Ability to pick up slack, even if it goes outside the job description
- Enjoys pair programming
- Willingness to learn more about machine learning research
- Concern for societal impacts of work
- High performance, large-scale ML systems experience
- Designing and implementing kernels for TPUs or other ML accelerators
- Deep understanding of accelerators, e.g., background in computer architecture
- Experience with ML framework internals
- Experience with language modeling with transformers
- Bachelor’s degree or equivalent combination of education, training, and/or experience
Responsibilities
- Identify and address performance issues across multiple ML systems, including research, training, and inference
- Design and optimize kernels for TPUs
- Provide feedback to researchers on how model changes impact performance
- Solve large-scale systems problems and low-level optimization
Technologies
TPUGPUML acceleratorsTransformersCustom collective communication algorithms
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