Sr. Applied Scientist, Ssg Science

Amazon Amazon · Big Tech · IN, KA, Bengaluru · Hardware Development

This role focuses on optimizing and fine-tuning Generative AI models for edge platforms, working closely with custom ML hardware. The scientist will train custom models, analyze deep learning workloads, and collaborate with cross-functional teams to build ML-centric solutions for consumer devices. The role also involves publishing research and presenting at ML conferences.

What you'd actually do

  1. Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms
  2. Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques
  3. Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine
  4. Train custom Gen AI models that beat SOTA and paves path for developing production models
  5. Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices

Skills

Required

  • building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning

Nice to have

  • modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • large scale distributed systems such as Hadoop, Spark etc.

What the JD emphasized

  • optimize for edge platforms
  • invent optimization techniques
  • map them to Amazon’s Neural Edge Engine
  • beat SOTA
  • build the best ML-centric solutions

Other signals

  • Edge AI
  • Model Optimization
  • Custom ML Hardware