Description

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.

Are you interested in shaping the future of entertainment? Do you want to invent, disrupt and redefine what entertainment means for fans, creators, and communities all around the globe?

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.

We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented creatives, technologists, marketing professionals and so much more, you can decide where a career with Prime Video takes you!

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

• Work closely with engineers and product managers to expand the depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps

• Provide technical and scientific guidance to your team members

• Stay up-to-date with advancements and the latest modeling techniques in the field

• Publish your research findings in top conferences and journals

About the team

Prime Video Personalization and Discovery science team owns different aspects of personalization algorithms, from user-item relevance, item-item relevance, and page composition, to name a few. We work closely with the engineering teams to put our models in production.

We are open to hiring candidates to work out of one of the following locations:

New York, NY, USA | Seattle, WA, USA | Sunnyvale, CA, USA

Basic Qualifications

• 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

Preferred Qualifications

• 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.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.