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# TPU Kernel Engineer

- **Company:** Anthropic's Mission
- **Location:** Seattle, United States
- **Salary:** $280,000.0
- **Contract:** Permanent contract
- **Skills:** Software Debugging, Machine Learning, Language Modeling, Pair Programming, Graphics Processing Unit (GPU), Large Language Models, Low Latency, Machine Learning Operations
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/tpu-kernel-engineer-anthropic-3-6784148

## About the Role

* Have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators
 * 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
 * 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

Representative projects:

 * Implement low-latency, high-throughput sampling for large language models
 * Adapt existing models for low-precision inference
 * Build quantitative models of system performance
 * Design and implement custom collective communication algorithms
 * Debug kernel performance at the assembly level, Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

## Description

As a TPU Kernel Engineer, you'll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimizing kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance. Strong candidates will have a track record of solving large-scale systems problems and low-level optimization.


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