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.
  

Your application is reviewed by real people.

Compensation Range: $150K - $300K