TPU Kernel Engineer: Optimize ML Systems at Scale

Anthropic; York and North Yorkshire; On-site; GBP 110,000 - 150,000; Full time

Benefits offered by this job

Health insurance

Dental & vision

Parental leave 22 weeks

Flexible PTO

Mental health support

Equity package

Relocation assistance

Home office stipend

Meals in office

Education stipend

Job summary

Anthropic in the United Kingdom seeks a TPU Kernel Engineer to identify and address performance issues across ML systems, including research, training and inference. You will design and optimize kernels for the TPU and provide feedback to researchers on how model changes impact performance.

You will implement low-latency, high-throughput sampling for large language models, adapt models for low-precision inference, and build quantitative models of system performance.

Qualifications

• Bachelor’s degree or equivalent experience required.
• Strong track record solving large-scale systems optimization.
• Experience optimizing ML systems on TPUs, GPUs or accelerators.
• Enjoy pair programming and collaboration.
• Understand accelerators and computer architecture.
• Knowledge of ML framework internals.
• Interest in ML research and societal impact.

Responsibilities

• Identify and address performance issues across ML systems (research, training, inference).
• Design and optimize kernels for the TPU.
• Provide feedback to researchers on model changes and performance impact.
• 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.

Skills

Large-scale systems

Low-level optimization

TPU optimization

GPUs & accelerators

Pair programming

Computer architecture

ML framework internals

Transformers / LMs

Societal impact awareness

Education

Bachelor's degree in related field

Job description

Anthropic in the United Kingdom seeks a TPU Kernel Engineer to identify and address performance issues across ML systems, including research, training and inference. You will design and optimize kernels for the TPU and provide feedback to researchers on how model changes impact performance.

You will implement low-latency, high-throughput sampling for large language models, adapt models for low-precision inference, and build quantitative models of system performance.