The Alexa Smart Home team is 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;
we are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected.
You can be part of a team delivering features that are highly anticipated by media and well received by our customers.
As an Applied Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home experiences using the latest Large Language Models (LLMs).
You will build products that your friends and family, along with millions of Alexa Smart Home customers use every day.
Key job responsibilities
- Develop new inference and training techniques to improve the performance of LLMs for Smart Home control and automation
- 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.
We are open to hiring candidates to work out of one of the following locations :
Seattle, WA, USA
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- 3+ years of building models for business application experience
- Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
PREFERRED QUALIFICATIONS
- Experience using Unix / Linux
- Experience in professional software development
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow
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