Senior Machine Learning Compiler Engineer

Amazon Amazon · Big Tech · Seattle, WA · Software Development

Senior Machine Learning Compiler Engineer responsible for the ground-up development and scaling of a deep learning compiler stack for Amazon's ML accelerators (Inferentia and Trainium). The role involves architecting and implementing business-critical features, optimizing neural net models for custom hardware, and integrating with ML frameworks like PyTorch and TensorFlow.

What you'd actually do

  1. Architecting and implementing business-critical features
  2. publish cutting-edge research
  3. mentoring a brilliant team of experienced engineers
  4. leverage your technical communications skill as a hands-on partner to Amazon ML services teams
  5. involved in pre-silicon design, bringing new products/features to market

Skills

Required

  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Experience as a mentor, tech lead or leading an engineering team

Nice to have

  • Bachelor's degree in computer science or equivalent
  • Machine Learning
  • AI accelerators

What the JD emphasized

  • ground-up development and scaling of a compiler
  • world's largest ML workloads
  • deep learning compiler stack
  • optimize the performance of complex neural net models
  • custom-built Amazon hardware

Other signals

  • ML accelerators
  • ML compiler
  • ML inference performance
  • ML training performance
  • Amazon Neuron SDK
  • PyTorch
  • TensorFlow
  • MxNet
  • optimize performance of complex neural net models
  • deep learning compiler stack
  • largest ML workloads