Anthropic· AI Research & Engineering· San Francisco, CA | New York City, NY | Seattle, WA
TPU Kernel Engineer
Classified Tasks (10)
Automate 0%Augment 100%Human-Only 0%
Augment (10)
AI assists, human decides
Identify performance bottlenecks in research, training, and inference ML systems.
analytical
Address performance issues across research, training, and inference ML systems.
technical
Design kernels for the TPU.
technical
Optimize kernels for the TPU.
technical
Provide feedback to researchers on how model changes impact system performance.
communication
Implement low-latency, high-throughput sampling for large language models.
technical
Adapt existing models for low-precision inference.
technical
Build quantitative models of system performance.
analytical
Design and implement custom collective communication algorithms.
technical
Debug kernel performance at the assembly level.
technical
Job description
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role 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. You may be a good fit if you: 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 The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $280,000 — $850,000 USD Logistics 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. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being