Applied Scientist

Job description

DESCRIPTION

“Alexa find me a job on the Alexa Knowledge team!”

Our focus in the Alexa Knowledge group combines natural language understanding, acquiring large volumes of structured knowledge, and building autonomous machine reasoning to allow our customers to get answers to their questions in the most natural way possible. We are part of a huge research and engineering effort on the Amazon Alexa organisation.

We have solved many complex problems to get to where we are today, but there are still plenty of challenges ahead of us, and Alexa is getting smarter every day. The problems we solve in the Alexa Knowledge group in Cambridge help Alexa get smarter by understanding the different ways people talk, by learning more and more facts about the world, by improving her common sense reasoning and by responding in the most natural way possible in multiple languages. We set out to build Alexa at Amazon because we believe that voice will fundamentally improve the way people will interact with technology, and we wanted to create a computer that could be controlled entirely by your voice.

In the Knowledge Extraction and Understanding team, we are constantly making Alexa smarter by enabling her to learn about what is happening in the world. We use multiple Machine Learning and Natural Language Processing techniques to enable learning and reasoning across a range of unstructured data sources, at internet-level scale. This requires methods that lie beyond the cutting edge academic and industrial research of today. The scope of this role is broad, covering a diverse range of problem space that include, but are not limited to fact extraction from unstructured text, large-scale categorisation, supervised, weakly supervised or self-supervised learning methods etc.

As an applied scientist, you will bring academic and/or industrial practical experience of solving hard problems through developing state of the art research methods. You will have the opportunity to guide junior scientists, and others interested in research. You will also have the opportunity to learn from some of the best researchers in the field, and be challenged by the engineering discipline needed to enable Alexa to operate at a global scale.

PREFERRED QUALIFICATIONS

· Ability to convey rigorous mathematical concepts and considerations to non-experts
· 2+ years post-PhD relevant industrial research experience
· Experience of working with large datasets and scaling ML models, and/or information extraction from unstructured sources

Desired profile

BASIC QUALIFICATIONS

· PhD Degree in Computer Science, Machine Learning, Computational Linguistics, Natural Language Processing, Applied Mathematics or a related field
· Strong academic record of refereed publications in top tier conferences or journals
· Hands-on experience in one or more of: Information Extraction, Scalable Machine Learning, Semantic Parsing, Natural Language Generation
· Deep Learning for NLP
· Active member of the research community
· Experience of building ML and NLP models in Python
· Excellent communication skills and the ability to working in a team