Machine Learning - Compiler Engineer , Aws Neuron, Annapurna Labs

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

Software Engineer role focused on building and optimizing the AWS Neuron compiler for custom AI chips (Inferentia and Trainium). The role involves transforming ML models (PyTorch, TensorFlow, JAX) into optimized code for these accelerators, with a focus on large language models and diffusion models. Requires strong software engineering skills, particularly in C++, and experience with compiler technologies is preferred.

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 state of the art ML models from our customers on AWS accelerators with optimal cost/performance benefits.
  3. You will have opportunity to work with open-source software (e.g., StableHLO, OpenXLA, MLIR) to pioneer optimizing advanced 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

Nice to have

  • compilers
  • building ML models using ML frameworks on accelerators
  • OpenXLA
  • StableHLO
  • MLIR

What the JD emphasized

  • Experience in object-oriented languages like C++/Java is a must

Other signals

  • optimizing ML models on custom hardware
  • compiler optimization for LLMs and diffusion models
  • transforming ML models for deployment on accelerators