Performance engineer

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 Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you’ll be responsible for identifying these problems and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large‑scale systems problems and will be excited to grow to become an expert in ML also.
Key qualifications 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, even if it goes outside your job description.
Enjoy pair programming.
Want to learn more about machine learning research.
Concern about the societal impacts of your work.
Experience with high‑performance, large‑scale ML systems.
GPU/Accelerator programming experience.
Experience with ML framework internals.
OS internals knowledge.
Language modeling with transformers.
Representative projects Implement low‑latency, high‑throughput sampling for large language models.
Implement GPU kernels to adapt our models to low‑precision inference.
Write a custom load‑balancing algorithm to optimize serving efficiency.
Build quantitative models of system performance.
Design and implement a fault‑tolerant distributed system running with a complex network topology.
Debug kernel‑level network latency spikes in a containerized environment.
Compensation Annual salary: $280,000 — $850,000 USD.
Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience. Field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience. Minimum experience: Minimum years of experience will correlate with the internal job level requirements for the position. Location: Hybrid policy: Staff are expected to be in our offices at least 25% of the time. Visa sponsorship: We sponsor visas and will make every reasonable effort to help with immigration for successful candidates.

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