Alexa is the groundbreaking voice service that powers Echo and other devices designed around your voice. Our team is creating the science and technology behind Alexa. We’re working hard, having fun, and making history. Come join our team! You will have an enormous opportunity to impact the customer experience, design, architecture, and implementation of a cutting edge product used every day by people you know.

We’re looking for a passionate, talented, and inventive graduate student to help build industry-leading conversational technologies that customers love. Our team’s mission is the enable Alexa to understand sounds and vocalization beyond speech. As an Applied Science Intern, you will work with talented applied scientists to develop novel algorithms and modeling techniques to advance the state of the art in audio processing and speech recognition. Your work will directly impact our customers in the form of novel products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in speech and language technology.

BASIC QUALIFICATIONS

· A Ph.D. student in Computer Science, Electrical Engineering or related field or a master student in Computer Science, Electrical Engineering or related field with a strong publication records

· Proficient with Python or Matlab

· Familiarity with audio and speech signal processing, speech recognition, or machine learning

· Good written and spoken communication skills.

PREFERRED QUALIFICATIONS

· A Ph.D. student in Computer Science, Electrical Engineering or related field with a specialization in speech recognition, audio, acoustic and speech processing or deep learning

· Solid publication records

· Strong technical curiosity

· Proficient with Python and C++/Java.

Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age

Perspective candidates are encouraged to send their CVs to:

Tao Zhang, Ph.D.

Senior Manager of Applied Science

Alexa Edge ML