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Applied Science Manager


Cambridge, United Kingdom


Are you interested in making Alexa smarter?

You: “Alexa, I’m looking for a job where I can build products straight out of science fiction.”
Alexa: “I have found matching jobs for you in the Alexa Knowledge team in Cambridge, UK. What role are you looking for?”
You: “I’d like to work on making you even smarter than you are today.”
Alexa: “Wonderful. There are multiple roles in Cambridge where you can do that, here are the details … “

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 a central 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. The problems we solve in the Alexa Knowledge team in Cambridge help Alexa get smarter by understanding the different ways people talk to Alexa; by learning more facts about the world; by improving her common sense reasoning and by responding in the most natural way possible in multiple languages.

In the Knowledge Extraction and Understanding team, we make Alexa smarter by improving her ability to understand intents of the user from text utterances, and enabling her to learn by extracting knowledge from a range of structured and unstructured sources.
As an Applied Science Manager on the team, your role is to manage a hybrid team of scientists and engineers to bring research and innovation into a production environment where the millions of customers that use Alexa can benefit from the team’s work each and every day.

Position Responsibilities:
· Leading strategic projects that include highly talented science teams responsible for developing and owning complex algorithms that go beyond the state of the art.
· Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications.
· Interact with business and software teams to understand their business requirements and operational processes.
· Actively participate in creating the right culture and environment ensures a diverse group of people and skillsets can flourish and deliver true breakthrough science that delivers innovation in production with regular real impactful benefits to users.
· Frame business problems into scalable solutions.
· Adapt existing and invent new techniques for solutions.
· Create and track accuracy and performance metrics.
· Inculcate a culture of innovation and operational efficiency in the organization.
· Influence, collaborate and communicate effectively with various leaders in Amazon.
· Hiring, growing and retaining a strong team keeping with the Amazon high bar.
· Be a scientific subject matter expert resource for other teams within Alexa Knowledge, and Amazon Research Cambridge.


· An MSc or PhD (preferred) in machine learning, operations research, applied mathematics, Natural Language Processing or a related field.
· Experience of managing others, preferably engineers and/or scientists.
· Hands-on experience in predictive modeling and analysis.
· Experience of building predictive and optimization models with knowledge of commonly used ML languages (MATLAB, Python, R).
· Knowledge of software engineering practices.
· Expert knowledge in at least one of following fields: machine learning, operations research, natural language processing
· A record of hiring or developing strong technical team members and leaders.
· Track record of generating intellectual property (patents, publications).
· Leadership, project planning and execution skills.
· Ability to communicate clearly with technical and non-technical stakeholders at all levels.
· Strong written communication skills.
· Natural curiosity and desire to learn.
· Ability to think and react in a high-energy, fast paced environment


· Track record of managing and growing interdisciplinary teams involving scientists and engineers.
· Demonstrate proactive technical leadership, strong verbal and written communication skills, and a proven ability to multi-task and manage stress effectively in a fast-paced environment.
· Experience with big data and analytics.
· Experience designing and supporting large-scale distributed systems in a customer facing production environment.


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