Sr. Applied Scientist, SSG Science
Amazon · Bangalore, India · Hardware Development
senior
machine learning
Applied Scientist
ic
3+ yrs Master's
· Posted Oct 28, 2025
Skills
AI Summary
Optimize generative AI models for edge devices through quantization, pruning, and distillation techniques. Collaborate with hardware architects and compiler engineers to deploy state-of-the-art models on Amazon's Neural Edge Engine. Requires 3+ years ML experience and expertise in deep learning frameworks.
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.
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.
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
- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
Preferred Qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.