Performance Engineer
San Francisco, CA | New York City, NY | Seattle, WA
Posted 16d ago
Remote Work Policy
On-site
Categories
Applied AI Engineer
About the job
Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. As a Performance Engineer, you will identify and solve novel systems problems that arise from running machine learning (ML) algorithms at scale. You will develop systems to optimize the throughput and robustness of our largest distributed systems. This role requires a strong track record of solving large-scale systems problems and a desire to become an expert in ML.
Responsibilities
- Identify novel systems problems in large-scale ML algorithm execution.
- Develop systems to optimize throughput and robustness of distributed systems.
- Implement low-latency, high-throughput sampling for large language models.
- Implement GPU kernels for low-precision inference.
- Write custom load-balancing algorithms for serving efficiency.
- Build quantitative models of system performance.
- Design and implement fault-tolerant distributed systems.
- Debug kernel-level network latency spikes in containerized environments.
Requirements
- Significant software engineering or machine learning experience, particularly at supercomputing scale.
- Results-oriented with a bias towards flexibility and impact.
- Ability to pick up slack and work outside of job description.
- Enjoy pair programming.
- Desire to learn more about machine learning research.
- Care about the societal impacts of your work.
- Experience with high-performance, large-scale ML systems.
- Experience with GPU/Accelerator programming.
- Experience with ML framework internals.
- Experience with OS internals.
- Experience with language modeling using transformers.