Have you ever wondered how we give voice to devices — even when they're offline? The Text-to-Speech on Device team at Amazon builds AI-powered voice models that run locally on hardware with limited resources, serving customers across Alexa, automotive, and accessibility experiences for visually impaired users. We sit at the intersection of speech generation, generative AI, and on-device machine learning, and we're looking for a curious, collaborative Applied Scientist to help us push what's possible.

In this role, you will research and develop production-ready speech generation models optimized for constrained environments. You will work across the full model lifecycle — from early experimentation and prototyping through to integration on real devices. If you're excited about solving hard scientific problems that directly improve how millions of people interact with technology, we'd love to hear from you.

Key job responsibilities
- Design and develop end-to-end machine learning models for on-device speech generation, from early research and experimentation through production-ready deployment.
- Research and apply advanced techniques in generative AI, model compression, and knowledge distillation to deliver high-quality voice models within tight hardware constraints.
- Propose and validate novel scientific approaches by authoring detailed technical specifications and contributing to peer-reviewed publications when appropriate.
- Evaluate model performance rigorously, identify improvement opportunities, and iterate on training and inference pipelines to optimize quality and efficiency.
- Collaborate with science and engineering teams across cloud and device platforms to bring speech generation capabilities from research prototypes to integrated product experiences.

About the team
The Text-to-Speech on Device team builds low-footprint AI models for speech generation that run locally on devices such as Android and FireOS platforms. Our models require significantly less computation than cloud-hosted alternatives, enabling offline voice experiences for Alexa, automotive partners, and accessibility solutions. We work closely with device engineering teams and cloud-based speech science teams to deliver the best possible experience for our customers. Our focus in the coming years is expanding the range of voices and languages we support while continuing to improve naturalness and efficiency on constrained hardware.