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Applied Scientist

Applied Scientist

Job ID 
596356
Location 
US-MA-Cambridge
Posted Date 
1/19/2018
Company 
Amazon.com Services, Inc.
Position Category 
Machine Learning Science
Recruiting Team 
..

Job Description


Alexa is the cloud-based voice service that powers Echo and other devices designed around your voice. The Information team is focused on providing information and knowledge to Alexa’s customers. We are evolving Alexa into intelligent, indispensable companion that provides up to date, accurate information whenever our customers need it.
The Information team is looking for an Applied Scientist. You will work with software developers to design and implement algorithms and predictive models for understanding and responding to customer questions. You will 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. 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.



Basic Qualifications

  • Masters or PhD in Computer Science, Machine Learning, Statistics or a related quantitative field.
  • 2+ years of hands-on experience in applied machine learning, and predictive modeling and analysis.
  • Fluency in one or more modern programming languages such as Java, C# or C++.

Preferred Qualifications

  • PhD
  • Experience in building speech recognition and natural language processing systems (e.g. commercial speech products or government speech projects).
  • Solid Machine Learning background and familiar with standard speech and machine learning techniques.
  • Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
  • Solid software development experience.
  • Good written and spoken communication skills.

Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation