Applied Scientist II, SSG Science

Amazon Science; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Amazon Science in Bengaluru seeks a senior Applied Scientist to advance edge Gen AI models for Amazon devices. You will optimize, quantize, prune and finetune neural networks for edge platforms and collaborate with compiler engineers and hardware teams to deliver ML-centric solutions.

Applicants should hold a PhD or equivalent, with 4+ years in ML or CS, and a track record of publications or patents. Expect collaboration across hardware, software and product teams in a fast-paced environment.

Qualifications

• PhD or master's with significant research/industry experience in ML or related field.
• Experience publishing in top-tier conferences/journals.
• Proficiency in Java, C++, Python and related languages.

Responsibilities

• Quantize, prune, distill, and finetune Gen AI models for edge platforms.
• Understand and optimize for Amazon Neural Edge Engine.
• Analyze DL workloads and map to edge hardware.
• Collaborate with compiler engineers, hardware architects and product teams.
• Publish/open-source contributions and present at ML conferences (NeurIPS, ICLR, MLSys).

Skills

Algorithms & data structures

Numerical optimization

Parallel computing

Distributed computing

High-performance computing

Information Theory basics

Deep Learning theory

Calculus

Linear algebra

Education

PhD in CS/CE/ML or related field

Master's in CS/CE/ML with 4+ years experience

Tools

Java

C++

Python

Job description

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

• 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.