"Alexa find me a job on the Alexa Knowledge team!"
Our focus in the Alexa Knowledge team 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're part of a huge research and engineering effort on the Amazon Alexa team.
We've 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 team 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.
On the Alexa Knowledge team, we are constantly making Alexa smarter by enabling her to learn about what's going on in the world. We use many different techniques to enable learning and reasoning across a range of structured and unstructured data. We are constantly at the forefront of both research and engineering in understanding user demands and data sources, to extract the right knowledge, expand the range of, and how, Alexa accesses information all to improve Alexa and give users the best experience. We believe that the information to answer (almost) every question can be found somewhere on the internet, and not just in an encyclopedia. Our goal is to teach Alexa how to autonomously consume a wider range of texts and expand her Knowledge Graph to learn more about the world.
We use multiple Machine Learning and Natural Language Processing techniques to validate the information extracted from various structured and unstructured 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 verification, natural language inference, large-scale categorisation, weakly supervised or self-supervised learning methods etc. As a senior scientist, you will bring academic and/or industrial practical experience and create novel solutions to complex problems. You will guide junior scientists, collaborate with the best researchers in the field and work with the engineering team to bring your solutions to the millions of customers who use Alexa every day.
• PhD degree in Computer Science, Machine Learning, Computational Linguistics, Natural Language Processing, Semantic Web, Applied Mathematics or a related field;
• Hands-on experience in one or more of: Information Extraction, Knowledge Fusion, Fact Verification, Deep Learning, Scalable Machine Learning;
• Active member of the research community and strong track record of scientific publications in premier journals or conferences;
• Experience of building ML and NLP models in Python;
• Good coding skills, experience in Python or Java is a plus;
• Ability to work on ambiguous problem areas and deliver business critical solutions.
• Track record of leading projects and/or building research agendas
• Excellent communication skills (both with technical and non-technical audiences) and the ability to working in a team
• Experience in mentoring junior scientists
• 5+ years of post-PhD relevant academic or industrial research experience;
• Experience with delivering production AI systems;
• Experience of working with large datasets;
• Expertise in fact verification, entity resolution, and knowledge fusion;