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Amazon Cambridge Development Center
Volné pracovní pozice: 58
Work on future delivery systems, revolutionary voice services, or groundbreaking devices
Amazon's innovative Cambridge, UK Development Center holds teams focused on three pioneering areas: Prime Air, Amazon Alexa, and Amazon Devices. Come and join us in the "Silicon Fen." You will have the opportunity to work on cutting-edge technology while enjoying the culture of a beautiful university town! Read more about our teams below.
Amazon Prime Air is a future delivery system designed to safely get packages to customers in 30 minutes or less using small unmanned aerial vehicles, also called drones. Flying under 400 feet and weighing less than 55 pounds, Prime Air vehicles will take advantage of sophisticated sense and avoid technology, as well as a high degree of automation, to safely operate beyond the line of sight to distances of 10 miles or more.
Prime Air’s Cambridge, UK office is focused on flight testing and operations related to this future service. The Cambridge team is comprised of both hardware and software engineering, as well as flight test safety leads and vehicle operators. Meet Daphne, a Technical Program Manager on the team, and Samuel, Chief Flight Test Engineer.
The Cambridge team plays 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. The Amazon Alexa team focuses on bringing voice-activated experiences to Amazon customers. The team first began with the development of Amazon Echo, a new category of device designed entirely around your voice. It's always ready, connected, and fast — just ask for information, music, news, weather, and more. To learn more about the Alexa team, watch our video!
- Alexa knowledge
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. Meet Stuart, a Software Development Manager and Craig, the Head of applied science.
- Alexa Machine Learning
The Alexa Machine Learning team is responsible for cutting-edge research and development in all aspects of human language technology, including automatic speech recognition (ASR) and natural language understanding (NLU). We are a team of world-class scientists that use many real-world data sources to build highly scalable machine learning solutions at massive scale.To learn more about the Alexa science team, watch our video and meet Catherine, a Machine Learning Manager on the Alexa team.
Amazon Devices / Amazon Lab126
The R&D team in Cambridge is part of the Lab126 organization based in Sunnyvale, California and develops application, device and cloud software for Amazon’s consumer electronic devices. The Lab126 team’s mission is to deliver instant access to everything – digital or physical – from anywhere, via delightfully unique Amazon experiences that make life easier and more fun. The team tackles software for flagship devices like Kindle, Fire tablets, Fire TV, Dash, Echo and many more innovative products to come! Read the story of Cressida, a Senior Software Development Manager.
Core ML, Cambridge
The Core Amazon Machine Learning team in Cambridge develops innovative machine learning methods for the modeling and analysis of complex data. We collaborate closely with other science, engineering and product teams in Amazon in several application domains such as robotics, natural language understanding and many more. The particular research areas of the group are uncertainty quantification, data-efficient learning, streaming applications and privacy aware and deep learning. We focus on the mathematical and computational challenges that arise in these topics. Meet Neil, Director of Machine Learning.
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