Senior Applied Scientist, Alexa Smart Home

Come work with other scientists and software developers in Alexa Smart Home to design and build the next generation of Smart Home experiences using the latest multimodal Large Language Models (LLM's) and Computer Vision.

We are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances, electronics, and cameras and alerts when something unusual is detected. We are focused on making Alexa the user interface for the home, from the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment. You can be part of a team delivering features that are highly anticipated by media and well received by our customers. And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day.

As a Senior Applied Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home control using the latest Large Language Models and Vision Language Models. And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day.

Key job responsibilities
- Develop new inference and training techniques to improve the performance of LLM's for Smart Home control and Automation
- Solve hard problems in computer vision, video summarization, and video search
- Develop robust techniques for synthetic data generation for training large models and maintaining model generalization
- Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done

About the team
We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence - with features like Alexa Hunches that automatically control Smart Home devices.
We are interdisciplinary and we act like it -- we ask each other questions and value our different perspectives.