Applied Scientist – Amazon Voice Shopping
Seeking Applied Researchers to build the future of the Voice Shopping Experience at Amazon. At Amazon Voice and Advanced Natural Shopping, we strive to enable shopping in everyday life. We allow customers to instantly order whatever they need, by simply interacting with their smart devices such as Echo, Fire TV, and beyond. Our services allow you to shop, anywhere, easily without interrupting what you're doing – to go from "I want" to "It's on the way" in a matter of seconds. We are seeking the industry's best applied scientists to help us create new ways to shop. Join us, and help invent the future of everyday life. The products you would envision and craft require ambitious thinking and a tireless focus on inventing solution to solve customer problems. You must be passionate about creating algorithms and models that can scale to hundreds of millions of customers, and insanely curious about building new technology and unlocking its potential.
Amazon Voice & Advanced Natural Shopping is seeking an Applied Scientist who will partner with technology and business leaders to build new state-of-the-art algorithms, models and services that surprise and delight our voice customers. As part of the new Applied Voice Research team you will use ML techniques such as deep learning to create and put into production models that deliver personalized shopping recommendations, allow to answer customer questions and enable human-like dialogs with our devices.
The ideal candidate will have a PhD in Mathematics, Statistics, Machine Learning, Economics, or a related quantitative field, and 3+ years of relevant work experience, including:
- Proven track record of achievements in natural language processing, search and personalization.
- Expertize on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametrics methods.
- Experience in Structured Prediction and Dimensionality Reduction.
- Strong fundamentals in problem solving, algorithm design and complexity analysis.
- Proficiency in at least one scripting languages (e.g. Python) and one large-scale data processing platform (e.g. Hadoop, Hive, Spark).
- Experience with using could technologies (e.g. S3, Dynamo DB, Elastic Search) and experience in data warehousing.
- Strong personal interest in learning, researching, and creating new technologies with high commercial impact.
- Track record of peer reviewed academic publications.
- Strong verbal/written communication skills, including an ability to effectively collaborate with both research and technical teams and earn the trust of senior stakeholders.
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