Senior Applied Scientist, Aws Neuron Science Team

Amazon Amazon · Big Tech · Cupertino, CA · Research Science

Senior Applied Scientist role at AWS Neuron Science team focusing on enhancing the software stack for Trainium and Inferentia accelerators. The role involves working with customers to identify adoption barriers, collaborating with engineering teams on solutions, and engaging with research communities. Key areas include AI for Systems (kernel/code generation, optimization), Machine Learning Compiler, System Robustness (accuracy/reliability validation), and Efficient Kernel Development for ML accelerators. The team supports large-scale customers and internal AWS services.

What you'd actually do

  1. Develop and apply ML/RL approaches for kernel/code generation and optimization
  2. Create advanced compiler techniques for ML workloads
  3. Build tools for accuracy and reliability validation
  4. Design high-performance kernels optimized for our ML accelerator architectures

Skills

Required

  • building machine learning models for business application
  • applied research
  • Java
  • C++
  • Python
  • neural deep learning methods
  • machine learning

Nice to have

  • R
  • scikit-learn
  • Spark MLLib
  • MxNet
  • Tensorflow
  • numpy
  • scipy
  • large scale distributed systems
  • Hadoop
  • Spark

What the JD emphasized

  • 3+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience
  • Experience with neural deep learning methods and machine learning

Other signals

  • AWS Trainium and Inferentia accelerators
  • ML compiler
  • kernel optimization
  • customer adoption
  • large scale distributed systems