Sr Applied Scientist, Hardware Devices Science Team

Description

Amazon Devices is an inventive research and development company that designs 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 Hardware division 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 Machine Learning Hardware based on a revolutionary architecture.

Work hard. Have Fun. Make History.

Key job responsibilities
What will you do?
- Engage in state-of-the-art and innovative research in areas such as Gen AI, model compression, and knowledge distillation
- Contribute to a novel and comprehensive training platform custom-tailored for preparing models for edge applications
- Invent optimization techniques to push the boundaries of deep learning model training
- Derive research approaches from first principles via knowledge of Information Theory, Statistics, Scientific Computing, and Deep Learning Theory
- Create and propose detailed theoretical specifications for novel research ideas and directions, and rigorously justify their correctness
- Train custom Gen AI models that beat the 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 by cohesively unifying software and hardware
- Publish in open source and present on Amazon's behalf at key ML conferences - e.g. NeurIPS, ICLR, MLSys

An Ideal candidate would have:
- PhD in quantitative science field, e.g. Applied Mathematics, Statistics, Physics
- Experience with designing novel algorithms via optimization theory and constrained optimization
- Experience with applications of reinforcement learning to GenAI model training
- Experience with training of diffusion models
- Experience with mixture-of-experts (MoE) models

Basic Qualifications

- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience in building machine learning models for business application
- Experience with neural deep learning methods and machine learning
- Experience programming in Java, C++, Python or related language

Preferred Qualifications

- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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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