Sr. Machine Learning - Compiler Engineer Iii, Aws Neuron, Annapurna Labs

Amazon Amazon · Big Tech · Cupertino, CA · Software Development

Senior Software Engineer role focused on building and optimizing the AWS Neuron compiler for AWS Inferentia and Trainium chips. The role involves transforming ML models (PyTorch, TensorFlow, JAX) into optimized implementations for deep learning workloads, with a focus on large language models and vision transformers. Responsibilities include compiler optimization, working with chip architects, and contributing to open-source communities.

What you'd actually do

  1. You will design, implement, test, deploy and maintain innovative software solutions to transform Neuron compiler’s performance, stability and user-interface.
  2. You will work side by side with chip architects, runtime/OS engineers, scientists and ML Apps teams to seamlessly deploy cutting edge ML models from our customers on AWS accelerators with optimal cost/performance benefits.
  3. You will have opportunity to become front-face of Neuron Compiler to work with open-source communities (e.g., StableHLO, OpenXLA, MLIR) and influence industry wide partners to pioneer optimizing cutting-edge ML workloads on AWS software and hardware.
  4. You will also work on building innovative features that will deliver best possible experiences for our customers – developers across the globe.

Skills

Required

  • C++
  • Java
  • compiler development
  • ML model optimization
  • performance tuning

Nice to have

  • PyTorch
  • TensorFlow
  • JAX
  • OpenXLA
  • StableHLO
  • MLIR
  • GPU programming

What the JD emphasized

  • building next generation Neuron compiler
  • solving hard compiler optimization problems
  • understand how these models work inside-out
  • Experience in object-oriented languages like C++/Java is a must

Other signals

  • optimizing ML models on custom hardware
  • compiler optimization for LLMs and vision models
  • performance and stability of ML inference