Within Amazon Alexa, the Alexa Knowledge team combines developing natural language processing and machine techniques and applying them across large volumes of data. To understand what users are asking, which data sources contain knowledge to improve Alexa answers, extracting that knowledge and formulating the right response. We build autonomous systems at scale and are 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 are breaking boundaries by allowing users to access information and services today through voice, with many more exciting projects in the pipeline.
In the Knowledge Extraction and Understanding group, we are constantly making Alexa smarter by enabling her to learn about what's going on in the world. We use multiple Machine Learning and NLP 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. The scope of the teams in the Knowledge Extraction and Understanding group is broad, covering a diverse range of problem spaces that include, but are not limited to semantic understanding, structured data extraction, fact extraction and verification from unstructured text, natural language generation, machine translation, model adaptation, large-scale categorisation and ranking. What's more, we do it at scale, to bring all those solutions to millions of customers that use Alexa every day.
We develop technology that combines natural language understanding, acquiring large volumes of structured knowledge, and machine reasoning to allow our customers to get answers to their questions in the most natural way possible. We play a key role in the development of Alexa; Amazon's cloud based voice service which delights customers on products such as Echo and Fire TV.
We're looking for a Principal Research Scientist to join our rapidly expanding group in Cambridge, England to help us achieve those goals. The ideal candidate is clearly passionate about new opportunities and has a demonstrable track record of success. A keen sense of ownership, effective teamwork and strong communication skills are absolute requirements. We are looking for leaders in the field. As a successful Principal Applied Scientist in the group you will mentor a group of scientists, ranging from post-doc level up to very senior scientists. You'll utilise a range of methods across the NLP and ML domains, help drive innovation through publications at leading conferences, and bring step-changes to a range of products through impactful results. You will be challenged by a strong team and get to work across areas spanning across the spaces of text analytics, semantics, deep neural networks, machine translation, natural language generation, search, ranking and many other areas that are key to enriching the Alexa experience. All problems are large scale, and require new approaches to achieve our ambitious goals.
• Ph.D. degree in Computer Science, Computer Engineering, Machine Learning, or related field
• Typically requires 10+ years of relevant work experience
• Excellent publication record of ML and NLP at major conferences that shows breadth and depth
• Recognized as a leader in area of specialty (machine learning, Natural Language Processing, etc.)
• Proven track record of mentoring and developing other researchers
• Strongly desirable to be proficient in more than one more major programming languages (C++, Java, C#, C, , Perl/Ruby, etc.)
• Expert knowledge in model evaluation and performance, operationalization and scalability of scientific techniques and establishing decision strategies.
• Industry experience showing research results being deployed at scales
• Experience building and delivering models for complex systems that leverage our technology platform and work well with other company systems
• Specific leadership in Question-Answering, Unstructured Text Extraction and/or Natural Language Generation