Do you want to revolutionize machine learning on edge devices? Join our team developing best in class customer experience that enables 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 help get AI experiences for customers on edge devices. 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.
Key job responsibilities
As an Applied Scientist on the Edge AI ML team, you will:
- 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
The long term vision of the Tablet Edge AI team is to build a scalable hybrid edge-cloud orchestration framework with Agentic capabilities that enable context aware personalized experiences for customers. We envision a future where customer experiences transcend traditional app-centric models, evolving into natural, context-aware, and autonomous interactions.
