Machine Learning Engineer, Prime Video Ads CX
Listed on Amazon’s official careers site. Posted September 27, 2026. Check that it is still open and apply there.
Apply on Amazon’s careers site →Job description
Are you interested in shaping the future of movies and television, and being part of a team that is helping Amazon redefine the future of video advertising? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. Video Advertising is rapidly evolving as customers shift their viewing experiences from traditional linear TV to streaming via connected devices, and Prime Video is a rising player in this space.
PV Ads CX team owns personalizing Ads experience for a customer on Prime Video. We work on balancing customer satisfaction and engagement with monetization objectives by applying machine learning based solutions to customize the Ads experience. We work with millions of customer's data to understand customer behavior, business need, and formulate ML based solution to delight our customers.
Successful candidates have a solid background in machine learning. They have experience working on big data, and neural network models. They have experience owning and maintaining highly-available, mission-critical systems. Experience in Advertising domain is a plus. You will need to have strong problem-solving and technical abilities, great communication skills, a motivation to learn, and achieve results in a fast-paced environment with excellent analytical reasoning skills.
Key job responsibilities
As a MLE-II on the team, you will be responsible for:
- Collaborating closely with Scientists to develop ML based solutions for Ads Customer Experience on Prime Video.
- Building solutions to process massive data, scale machine learning models, while defining and optimizing criteria critical to the success of the customer experience
- Driving cross-team initiatives and leading a team of developers on key initiatives.
- Mentoring engineers on the team.
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