Amazon Senior Applied Scientist Prime Video - Personalization Discovery Science 

United States, Washington, Seattle 

935842583

Prime Video offers customers a vast collection of movies, series, and sports—all available to watch on hundreds of compatible devices. U.S. Prime members can also subscribe to 100+ channels including Max, discovery+, Paramount+ with SHOWTIME, BET+, MGM+, ViX+, PBS KIDS, NBA League Pass, MLB.TV, and STARZ with no extra apps to download, and no cable required. Prime Video is just one of the savings, convenience, and entertainment benefits included in a Prime membership. More than 200 million Prime members in 25 countries around the world enjoy access to Amazon’s enormous selection, exceptional value, and fast delivery.As part of the Prime Video team, you’ll get to work on projects that are fast-paced, challenging, and varied. Also, you’ll get to experiment with new possibilities, take risks, and collaborate with remarkable people.As a member of the Prime Video Personalization organization, you will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide.Key job responsibilities
- Develop ML models for various PV search systems using deep learning, GenAI, Reinforcement Learning, and optimization methods
- Stay up-to-date with advancements and the latest modeling techniques in the field
- Publish your research findings in top conferences and journals

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.