Research Scientist, SSG Science
Job Description
Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional early career research scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History.Key job responsibilitiesKey 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
Locations
- India, KA, Bengaluru, Bengaluru, KA, India
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
80,000 - 150,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - PhD, or a Master's degree and experience with popular deep learning frameworks such as MxNet and Tensor Flowintermediate
- - Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithmsintermediate
- - Experience in Java, C++, Python, or a related languageintermediate
- - 1+ years of industry or academic research experienceintermediate
Required Qualifications
- - Bachelor's degree or above in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field (degree in above in engineering)
- - PhD, or a Master's degree and experience with popular deep learning frameworks such as MxNet and Tensor Flow (experience)
- - Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms (experience)
- - Experience in Java, C++, Python, or a related language (experience)
- - 1+ years of industry or academic research experience (experience, 1 years)
Preferred Qualifications
- - Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field (degree in engineering)
- - Experience with data modeling, warehousing and building ETL pipelines (experience)
- - Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience in software development (experience)
- - Experience in patents or publications at top-tier peer-reviewed conferences or journals (experience)
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
