Senior Distributed Systems Engineer

Palo Alto, California

Luma AI

Building visual AI to expand human imagination and capabilities

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We are looking for people with strong ML & Distributed systems backgrounds. This role will work within our Research team, closely collaborating with researchers to build the platforms for training our next generation of foundation models.

Responsibilities

  • Work with researchers to scale up the systems required for our next generation of models trained on multi-thousand GPU clusters.
  • Profile and optimize our model training code-base to achieve best in class hardware efficiency.
  • Build systems to distribute work across massive GPU clusters efficiently.
  • Design and implement methods to robustly train models in the presence of hardware failures.
  • Build tooling to help us better understand problems in our largest training jobs.

Experience

  • 5+ years of work experience.
  • Experience working with multi-modal ML pipelines, high performance computing and/or low level systems.
  • Passion for diving deep into systems implementations and understanding their fundamentals in order to improve their performance and maintainability.
  • Experience building stable and highly efficient distributed systems.
  • Strong generalist Python and Software skills including significant experience with Pytorch.
  • Good to have experience working with high performance C++ or CUDA.
  • Please note this role is not meant for recent grads.

Compensation

  • The pay range for this position in California is $180,000 - $250,000yr; however, base pay offered may vary depending on job-related knowledge, skills, candidate location, and experience. We also offer competitive equity packages in the form of stock options and a comprehensive benefits plan. 
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Category: Engineering Jobs

Tags: CUDA Distributed Systems GPU HPC Machine Learning Model training Pipelines Python PyTorch Research

Perks/benefits: Competitive pay Equity / stock options

Region: North America
Country: United States

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