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 the Amazon Hardware division in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for an exceptional Sr. Applied Scientist to join our 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.
Key job responsibilities
- Mentor less experienced Applied Scientists
- 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
This is an exciting opportunity to join the Amazon Hardware division in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for an exceptional Sr. Applied Scientist to join our 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.
Key job responsibilities
- Mentor less experienced Applied Scientists
- 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