Do you want to revolutionize machine learning for edge devices? Join our team developing cutting-edge compression algorithms that enable AI models to run efficiently on resource-constrained hardware. Our work is transforming the way Amazon customers interact with our devices, creating novel experiences that push the boundaries of what's possible with AI.
About the role:

As an Applied Scientist on the Edge AI & ML team, you will be at the forefront of innovation, working on technology that directly impacts millions of Amazon customers. Our team is pioneering new approaches that achieve an order of magnitude higher compression rates compared to existing methods. You'll work on challenging problems at the intersection of deep learning, optimization, and systems.
By optimizing ML models for edge deployment, we're bringing advanced AI closer to our customers, enhancing privacy, reducing latency, and enabling new features that were previously impossible.

Your work will:

- Power the next generation of Amazon devices with efficient, on-device AI
- Enable novel customer experiences that respond in real-time, even without internet connectivity
- Push the boundaries of what's possible with edge computing and machine learning

Key job responsibilities
As an Applied Scientist on the Edge AI ML team, you will:

- Develop and implement novel algorithms for compressing and optimizing deep learning models for edge devices
- Conduct experiments to evaluate and benchmark model performance across various hardware platforms
- Collaborate with product teams to integrate our technology into Amazon devices and services
- Innovate on techniques to achieve state-of-the-art efficiency in AI model deployment
- Explore and adapt emerging ML architectures (e.g., transformers, neural architecture search) for edge computing
- Investigate hardware-aware ML techniques to tailor models for specific edge devices


About the team
Our team is at the forefront of enabling AI capabilities on edge devices. We offer:

- The opportunity to work on cutting-edge ML technologies with real-world impact
- Collaboration with world-class researchers and engineers
- A culture of innovation that encourages new ideas and approaches
- The scale and resources of Amazon to tackle ambitious technical challenges