
Research Scientist, SSG Science
3 weeks ago
Key job responsibilities
Key Job Responsibilities:
• Understand and contribute to model compression techniques (quantization, pruning, distillation, etc.) while developing theoretical understanding of Information Theory and Deep Learning fundamentals
• Work with senior researchers to optimize Gen AI models for edge platforms using Amazon's Neural Edge Engine
• Study and apply first principles of Information Theory, Scientific Computing, and Non-Equilibrium Thermodynamics to model optimization problems
• Assist in research projects involving custom Gen AI model development, aiming to improve SOTA under mentorship
• Co-author research papers for top-tier conferences (NeurIPS, ICLR, MLSys) and present at internal research meetings
• Collaborate with compiler engineers, Applied Scientists, and Hardware Architects while learning about production ML systems
• Participate in reading groups and research discussions to build expertise in efficient AI and edge computing
BASIC QUALIFICATIONS
- Bachelor's degree or above in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field- Strong understanding of deep learning fundamentals, linear algebra and statistics.
- Experience working with deep learning frameworks such as Pytorch or Tensorflow.
- Proven experience in writing high-quality code in C/C++/Python.
- Prior academic or industrial research experience is required.
PREFERRED QUALIFICATIONS
- Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field- Hands-on experience with model compression techniques (quantization/pruning/distillation).
- Experience training or fine-tuning large language models.
- Publications at top-tier conferences (NeurIPS, ICLR, ICML).
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