Applied Scientist - Automatic Speech Recognition in Aachen, Deutschland

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 understanding.

We are hiring in all areas of spoken language understanding with a special focus on acoustic modeling, language modeling, finite state methods, etc.

Candidates should have a strong background 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.