Help create the future of advertising and digital entertainment with Amazon! It's an exciting time to be on the Video Shopping Experience (VSE) team. Amazon's Video Shopping Experience team has a problem: We have millions of videos that help millions of customers shop every day. These include product demos, customer reviews, buying guides, how-to's, and others. How do we choose the right videos to show to the right customers at the right time, to help them make the right shopping decision? That's where you come in. We need a strong Applied Scientist with experience in Machine Learning, Big Data, and Service Oriented Architecture, to be part of a team of talented engineers and scientists to solve this problem
As an applied scientist on the VSE's Ranking and Relevance team, you will build systems for cataloging, analyzing, ranking, and vending shopping related videos across Amazon. You will leverage your expertise in Machine Learning techniques to guide your team to deliver solutions at Amazon scale.
The ideal candidate will have hands-on experience as well as be able to make the right decisions about technology, models and methodology choices. You will strive for simplicity, and demonstrate significant creativity and high judgment backed by statistical proof.
This position in the Video Shopping Experience team presents a unique and rare opportunity to get in on the ground floor within a fast growing business and help shape the technology, product and the business.
We're looking for a whip smart engineer capable of using machine learning and statistical techniques to create state-of-the-art solutions for non-trivial, and arguably, unsolved problems. If you are results driven, know how to apply advanced Machine Learning techniques, love to work with video, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.
· Use statistical and machine learning techniques to create scalable solutions for video analysis and content moderation problems
· Analyze and extract information from large amounts of videos to help moderate and optimize search across videos
· Design, development and evaluation of highly innovative models for predictive learning
· Work closely with software engineering teams to drive real-time model implementations and new feature creations
· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
· Track general business activity and provide clear, compelling management reporting on a regular basis
· Research and implement novel machine learning and statistical approaches