Our team leads the development and optimization of on-device ML models for Amazon's hardware products, including audio, vision, and multi-modal AI features. We work at the critical intersection of ML innovation and silicon design, ensuring AI capabilities can run efficiently on resource-constrained devices.
Currently, we enable production ML models across multiple device families, including Echo, Ring/Blink, and other consumer devices. Our work directly impacts Amazon's customer experiences in consumer AI device market. The solutions we develop determine which AI features can be offered on-device versus requiring cloud connectivity, ultimately shaping product capabilities and customer experience across Amazon's hardware portfolio.
This is a unique opportunity to shape the future of AI in consumer devices at unprecedented scale. You'll be at the forefront of developing industry-first model architectures and compression techniques that will power AI features across millions of Amazon devices worldwide. Your innovations will directly enable new AI features that enhance how customers interact with Amazon products every day. Come join our team!
Key job responsibilities
As a Sr Applied Scientist on the Edge AI ML team, you will:
- Design and implement novel algorithms for compressing and optimizing deep learning models for edge devices at the system level
- Lead complex research projects from inception to production deployment
- Define technical requirements and develop implementation plans for large-scale ML systems
- Drive adoption of new approaches and best practices across teams
- Mentor and develop junior scientists while fostering collaboration across teams
- Conduct and oversee experiments to evaluate and benchmark model performance across various hardware platforms
- Partner with product teams to integrate our technology into Amazon devices and services
- Advance state-of-the-art efficiency in AI model deployment through novel research
- Lead exploration of emerging ML architectures (e.g., transformers, neural architecture search) for edge computing
- Drive innovation in hardware-aware ML techniques to tailor models for specific edge devices
- Author research publications and engage with the external scientific community when aligned with business goals
About the team
Our team is at the forefront of enabling AI capabilities on edge devices. We offer:
- The opportunity to lead 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
- Opportunities to influence product strategy and technical direction
