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Amazon.com Posted 5 months ago

Do you want to know about new movies and TV shows that you'll will enjoy the day they come out? So do millions of our customers, world wide. Did you know we have a wide range of niche content including Natural Park documentaries, Kung-fu movies, or Korean dramas on our service? No? Well, we're looking to change that. Come be part of history, as we fulfill Prime Video's vision of being customer's first place to find something to watch



We're using cutting edge approaches such as graph convolutional networks (GCNs) to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know exitsed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external ML conferences (e.g. https://dl.acm.org/citation.cfm?id=3292500.3330675).



At the end of the day, you will be innovating and experimenting in a complex technical and business space - dealing with Amazon scale, different types of video assets (Movies, TV Shows, Live Sports, Short Videos) and balancing various business offerings (Prime, Third party channels) - positively impacting millions of customers worldwide.



If you are ready to truly make an impact on a product that is used by millions of people around the world, including your own friends and family, then we would love to talk to you.

Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age



Basic Qualifications

· PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience

· 3+ years of experience of building machine learning models for business application

· Experience programming in Java, C++, Python or related language

· PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent);

· 3+ years of practical experience applying ML to solve complex problems;

· Algorithm and model development experience for large-scale applications;

· Experience using Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language;

· Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives

Preferred Qualifications · PhD in Computer Science (Machine Learning, AI, Statistics, Mathematics, or equivalent);

· 3+ years of practical experience applying ML to solve complex problems;

· Extensive knowledge and practical experience in deep neural networks and other recommendation systems, including: convolutional neural networks (CNNs), recurrent neural networks (RNNs), residual neural networks and collaborative filtering techniques;

· Significant peer reviewed scientific contributions in premier journals and conferences;

· Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar);

· Proven track record of production achievements, handling gigabyte and terabyte size datasets;

· Strong fundamentals in problem solving, algorithm design and complexity analysis;

· Strong personal interest in learning, researching, and creating new technologies with high customer impact;

· Experience with defining research and development practices in an applied environment;

· Proven track record in technically leading and mentoring scientists;

· Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts