Applied Scientist, SSG Science
Amazon · Sunnyvale, CA · Applied Science
mid
machine learning
Applied Scientist
ic
· Posted May 12, 2026
$171,600 – $222,200
USD per year
About this role
Amazon is hiring a mid-level Applied Scientist in the machine learning function based in Sunnyvale, CA. The posting calls out experience with Python, Java, LLMs, Deep Learning. Compensation is listed at $171,600–$222,200 per year.
- Role
- Applied Scientist
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Sunnyvale, CA
- Department
- Applied Science
- Posted
- May 12, 2026
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Job description
from Amazon careersAmazon 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
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.
Key job responsibilities
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
This is an excerpt. Read the full job description on Amazon careers →