Research Scientist, Ssg Science

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

Research Scientist role focused on developing and optimizing Generative AI models for edge devices, involving model compression techniques, custom ML hardware, and theoretical understanding of deep learning and information theory. The role involves co-authoring research papers and collaborating with cross-functional teams.

What you'd actually do

  1. Understand and contribute to model compression techniques (quantization, pruning, distillation, etc.) while developing theoretical understanding of Information Theory and Deep Learning fundamentals
  2. Work with senior researchers to optimize Gen AI models for edge platforms using Amazon's Neural Edge Engine
  3. Study and apply first principles of Information Theory, Scientific Computing, and Non-Equilibrium Thermodynamics to model optimization problems
  4. Assist in research projects involving custom Gen AI model development, aiming to improve SOTA under mentorship
  5. Co-author research papers for top-tier conferences (NeurIPS, ICLR, MLSys) and present at internal research meetings

Skills

Required

  • Bachelor's degree or above in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
  • PhD, or a Master's degree and experience with popular deep learning frameworks such as MxNet and Tensor Flow
  • Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
  • Experience in Java, C++, Python, or a related language
  • 1+ years of industry or academic research experience

Nice to have

  • Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience in software development
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals

What the JD emphasized

  • model compression techniques
  • optimize Gen AI models for edge platforms
  • custom Gen AI model development
  • top-tier conferences

Other signals

  • Gen AI on edge
  • edge models
  • model compression
  • optimize Gen AI models for edge platforms