Applied Scientist, SSG Science

Amazon Science; Bengaluru; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Amazon Science in Bengaluru is seeking exceptional scientists to join our Applied Science team and help develop the next generation of edge Gen AI models. You will work on quantizing, pruning, distilling, and finetuning models for edge platforms while collaborating with hardware and compiler teams.

The role requires strong backgrounds in ML, deep learning, and related math, with a track record of research publications or patents.

Qualifications

• 2+ years of building ML models for business applications.
• PhD, or Master's degree and 2+ years of applied research experience.
• Experience in patents or publications at top-tier peer-reviewed conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.
• Strong foundation in linear algebra, calculus, etc.

Responsibilities

• Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms.
• Understand Amazon's Neural Edge Engine to invent optimization techniques.
• Analyze deep learning workloads and map them to Neural Edge Engine.
• Use Information Theory, Scientific Computing, Deep Learning Theory, and Thermodynamics fundamentals.
• Train custom Gen AI models that beat SOTA for production.
• Collaborate with compiler engineers, Applied Scientists, Hardware Architects and product teams.
• Publish in open source and present at ML conferences (NeurIPS, ICLR, MLSys).

Skills

Machine learning

Python

Java/C++

Edge computing

Information Theory

Deep learning

Math foundations

Education

PhD

Master's degree

Tools

TensorFlow

PyTorch

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 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.

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 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 responsibilities
What will you do?

Key job responsibilities

What will you do?

• Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms
• Fundamentally understand Amazon's underlying Neural Edge Engine to invent optimization techniques
• Analyze deep learning workloads and provide guidance to map them to Amazon's Neural Edge Engine
• Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics
• Train custom Gen AI models that beat SOTA and paves path for developing production models
• Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices
• Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys.

Basic Qualifications

• 2+ years of building machine learning models for business application experience
• PhD, or Master's degree and 2+ years of applied research experience
• Experience in patents or publications at top‑tier peer‑reviewed conferences or journals
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing
• Strong foundation in relevant mathematical concepts (linear algebra, calculus, etc.)

Preferred Qualifications

• Experience in professional software development
• Prior experience in productionizing ML models and managing their full lifecycle from development to deployment

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