The Amazon Development Centre Cambridge UK is launching the 2019 internship program!
We have positions open across the different science teams, including Amazon Devices, Core Machine Learning, Alexa Knowledge and Alexa Machine Learning, Our offices are located close to the city centre, just 10 minutes cycle ride away from the central university colleges and departments.
Internships will be 12 weeks long, running from June to September, and interns will work closely with a mentor in one of our Cambridge teams. By partnering closely with our developers, you have the opportunity to work on cutting-edge technology and contribute to research which improves products for our customers.
The closing date for applications is the end of March 2019, and we will start interviewing in December 2018 until April 2019. Come and join us in the “Silicon Fen”!
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.
- 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.
- Alexa Machine Learning
The 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. Some examples are the scalability issues from training models in massive datasets, decision-making problems under uncertainty or surrogate modeling approaches, where some inaccessible process of interest is replaced by an emulator. Most of the methodologies that we use and develop have a probabilistic flavor. The team has a large expertise in Gaussian processes, approximate inference, probabilistic modeling, latent variable models, Bayesian optimization and representation learning among other related fields. We put all these technologies in service of Amazon to guarantee a better customer experience.
- Alexa text-to-speech
The Alexa text-to-speech group delivers the speech synthesis which drives Amazon's personal assistant: Alexa.
We are applying cutting-edge machine learning approaches to tackle issues in a wide-range of areas of text-to-speech synthesis. These include: linguistics, perceptual evaluation and acoustic modelling. The group is pushing the boundaries of speech synthesis research to develop voices in our growing range of languages, working to make sure interaction with Alexa is great amongst our growing number of devices. Amongst our current research is working towards making the voice of Alexa more aware of the content she is reading to allow her to be more engaging and natural.
As an intern within the text-to-speech team you will be put straight into the front-line of speech synthesis at Amazon and will work closely with your team to bring improvements which will be delivered straight to our customers.
Supply Chain Machine Learning, Cambridge
The Supply Chain 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 supply chain optimization, robotics, and natural language understanding. The particular research areas in the group are uncertainty quantification, data-efficient learning, streaming applications and privacy-aware machine learning. We focus on the mathematical and computational challenges that arise in these areas. Most of the methodologies we use and develop have a probabilistic flavor. The team has a large expertise in Gaussian processes, approximate inference, probabilistic modeling, latent variable models, Bayesian optimization, representation learning, differential privacy, and other related fields. We employ all these technologies to continually improving the experience of Amazon customers.
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!
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