Applied Scientist, SSG Science

Alternance Amazon

Bengaluru

On-site

INR 3,000,000 - 7,200,000

Full time

20 hours ago
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Job summary

Amazon Inc. seeks an exceptional scientist to join the Applied Science team to develop Gen AI on edge for consumer devices.

You will work on quantization, pruning, fine-tuning and optimization of models for edge platforms, collaborating with hardware architects and compiler engineers to push the frontier of edge ML. The role involves publishing at major ML conferences and contributing to a revolutionary architecture for AI on devices like Kindle, Fire TV and Echo.

Qualifications

  • 2+ years building models for business applications.
  • PhD or Master's with 4+ years in CS/CE/ML.
  • Experience in patents or publications at top-tier conferences or journals.
  • Proficient in Java, C++, Python or related language.

Responsibilities

  • Quantize, prune, distill, finetune Gen AI models for edge platforms.
  • Understand and optimize Amazon's Neural Edge Engine.
  • Map deep learning workloads to edge hardware and software.
  • Collaborate with compiler engineers, Applied Scientists and hardware teams.

Skills

Java
C++
Python

Education

PhD in CS/CE/ML
Master's degree in CS/CE/ML

Tools

Neural Edge Engine

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.
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 models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field 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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.

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