Machine Learning - Compiler Engineer Ii, Annapurna Labs

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

The Machine Learning Compiler Engineer II on the AWS Neuron team will support the development and scaling of a compiler for AWS Machine Learning accelerators (Inferentia and Trainium chips). This role involves architecting and implementing features for the AWS Neuron Software Development Kit (SDK), which optimizes neural network models for custom AWS hardware. The engineer will work with ML frameworks like PyTorch and TensorFlow, contributing to a toolchain aimed at improving ML performance.

What you'd actually do

  1. supporting the ground-up development and scaling of a compiler to handle the world's largest ML workloads
  2. Architecting and implementing business-critical features
  3. publish cutting-edge research
  4. contributing to a brilliant team of experienced engineers
  5. leverage your technical communications skill as a hands-on partner to AWS ML services teams

Skills

Required

  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language
  • 2+ years of experience architecting and optimizing compilers
  • Proficiency with 1 or more of the following programming languages: C++ (preferred), C, Python

Nice to have

  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent
  • PhD in computer science, computer engineering, or related field, or MS degree
  • Experience with multiple toolchains and Instruction Set Architectures
  • Proficiency with resource management, scheduling, code generation, and compute graph optimization
  • Experience optimizing Tensorflow, PyTorch or MxNET deep learning models
  • A background in Machine Learning and AI accelerators is preferred

What the JD emphasized

  • AWS Machine Learning accelerators
  • AWS Neuron Software Development Kit (SDK)
  • ML compiler, runtime
  • optimizing the performance of complex neural net models
  • deep learning compiler stack
  • scaling of a compiler to handle the world's largest ML workloads

Other signals

  • AWS Machine Learning accelerators
  • AWS Neuron Software Development Kit (SDK)
  • ML compiler, runtime
  • optimizing the performance of complex neural net models
  • deep learning compiler stack
  • scaling of a compiler to handle the world's largest ML workloads