Applied Scientist - Smart Home Machine Learning
- Seattle, WA
The 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 intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You will 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 software developers to design and implement algorithms and predictive models for how customers use and interact with smart devices in their homes. You will help lay the foundation to move from directed device interactions to learned behaviors that enable Alexa to pro-actively take action on behalf of the customer. And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Like the world of smart phones less than 10 years ago, this is a rare opportunity to have a giant impact on the way people live.
• PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
• 2+ years of experience of building machine learning models for business application
• Experience programming in Java, C++, Python or related language
• Master's or Ph.D. degree in Engineering, Computer Science, Machine Learning, Math, Statistics or related fields with specialization in speech recognition, natural language processing, and/or machine learning.
• Experience in experiment design and statistical analysis of results.
• Experience with R, MATLAB, Python or similar scripting language
• An understanding of machine learning, algorithms and computational complexity.
• Familiar with the core undergraduate curriculum of Computer Science.
• Algorithm development experience
• Technical fluency; comfort understanding and discussing architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members.
• Publications at top-tier peer-reviewed conferences or journals
• Familiar with the techniques and limitations of observational studies.
• Familiar with theory and practice of information retrieval, relevance, machine learning, and data mining.
• Skilled at data visualization and presentation.
• Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly in both verbal and written form.
• Energy and willingness to formulate, test, and discard or revise many hypotheses to help Amazon improve its product catalog.
• Theory and practice of Design of Experiments and statistical analysis of results.
• Ability to relate to and solve business problems through machine learning, data mining and statistical algorithms.
• Strong desire to push your ideas into production, overcoming obstacles, in order to benefit Amazon's customers.
Back to top