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    Performance Engineer - San Francisco, United States - Anthropic Limited

    Anthropic Limited
    Anthropic Limited San Francisco, United States

    1 week ago

    Default job background
    Description
    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.

    You may be a good fit if you:

    Have significant software engineering or machine learning experience, particularly at supercomputing scale

    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

    GPU/Accelerator programming

    ML framework internals

    OS internals

    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

    Deadline to apply:
    None. Applications will be reviewed on a rolling basis.

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