Machine Learning Performance Optimization Engineer

14 hours ago


Mountain View, Arkansas, United States Wayve Full time
About Wayve

Wayve is a leading developer of Embodied AI technology, pioneering advanced AI software and foundation models that enable vehicles to perceive, understand, and navigate complex environments. Our mission is to create autonomy that propels the world forward.

The Role

We are seeking a skilled Machine Learning Performance Engineer to join our Machine Learning Platform team, focusing on optimizing large-scale training jobs to scale our models through the next order of magnitude. The successful candidate will own our GPU training infrastructure and software abstractions, with a specific focus on improving training efficiency.

Key Responsibilities
  • Maximize the Mean Field Update (MFU) of our large-scale training jobs.
  • Profile and identify bottlenecks in training code.
  • Implement GPU kernels to improve training throughput.
  • Work closely with Research teams to integrate and test training efficiency improvements.
  • Owning and improving our GPU training clusters.
About You

We are looking for a highly experienced engineer with a strong background in performance optimization or ML engineering. Essential qualifications include:

  • 5+ years of experience in performance optimization or ML engineering.
  • Experience optimizing large-scale training jobs on GPU compute clusters.
  • Experience working in platform teams and with research teams.
  • Ability to write high-quality, well-structured, and tested Python code.
  • BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience.

Desirable qualifications include:

  • Solid experience working with concurrent, parallel, and distributed computing.
  • Experience using Nvidia NSight Systems.
  • Experience implementing GPU kernels.
  • Knowledge of computing fundamentals - what makes code fast, secure, and reliable.

We welcome applicants from diverse backgrounds and encourage those with unique skills and experiences to apply. This is a full-time role based in our office in Mountain View, California, with a hybrid working policy that combines time together in our offices and workshops with time spent working from home.



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