Interested in Amazon Alexa? We’re building the speech and
language solutions behind Amazon Echo and other Amazon products
and services. Come join us!
Amazon is looking for passionate, talented, and inventive
Scientists to help build world-leading Speech and Language
technology. Our mission is to create a delightful experience to
Amazon’s customers by advancing the state of the art in Automatic
Speech Recognition (ASR), Natural Language Understanding (NLU)
and Machine Learning (ML).
As part of our speech and language team, you will work alongside
internationally recognized experts to develop novel algorithms
and modeling techniques to build and advance state-of-the-art
spoken language understanding systems. Your work will directly
impact millions of our customers in the form of products and
services that make use of speech and language technology. You
will gain hands-on experience with Amazon’s heterogeneous speech,
text, and structured data sources, and large-scale computing
resources to accelerate advances in spoken language
We are hiring in all areas of spoken language understanding with a special focus on acoustic modeling, language
modeling, finite state methods, etc.
We will also consider candidates without
explicit prior experience in these fields, if they are strong in
machine learning, statistics, and coding, are eager to learn and
have a "can do" attitude.
As a Research Scientist on our team, you will build,
extend and optimize cutting-edge spoken language understanding
systems and conduct core research aimed at advancing the state of
the art. This involves:
- Researching the latest modeling techniques. Understanding trade-offs between competing approaches, and identifying the ones that are likely to have real impact on our customers.
- Implementing and improving modeling tools, training recipes and prototypes utilizing programming skills in Python, Java and/or C++.
- Conducting experiments to assess the quality of speech recognition and natural language processing models and to study the effectiveness of different modeling techniques.
- Analyzing field data in order to identify areas of possible improvement or enhancement of the system.
- Presenting and discussing ideas and results within the team and with internal stakeholders.