Amazon Devices is an inventive research and development company that designs and engineers high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo, and Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI to the 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, optimizing them in co-design with custom ML hardware based on a revolutionary architecture.
Key Responsibilities
What will you do?
- Quantize, prune, distill, and 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 exceed state-of-the-art and pave the way 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 such as NeurIPS, ICLR, and MLSys
Basic Qualifications
- Experience in building machine learning models for business applications
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python, or a 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.
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