Senior Applied Scientist , Prime Video Ads

Prime Video is a first‑stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios‑produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+.

All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.

Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best‑in‑class digital video experience.

As a Prime Video team member, you’ll have end‑to‑end ownership of the product, user experience, design, and technology required to deliver state‑of‑the‑art experiences for our customers. You’ll get to work on projects that are fast‑paced, challenging, and varied. You’ll also be able 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 technologists, you can decide where a career Prime Video Tech takes you!

Are you passionate about building intelligent systems that personalize experiences for hundreds of millions of customers? Do you want to work at the intersection of deep learning, causal inference, and product optimization, where your models directly shape how customers experience advertising on one of the world’s largest streaming platforms?

Prime Video Ads is redefining what ad‑supported streaming looks like. We launched ads on Prime Video in 2024 and are now building the science foundation to make our ad experience the most customer‑centric in the industry.

• Lead the research and development of ML models that personalize advertising decisions for 100M+ customers across 100k+ titles, with production deployment in mind.
• Develop deep learning architectures (multi‑task learning, embedding‑based representations) for customer behavior prediction at scale.
• Design and analyze large‑scale A/B experiments, applying causal inference techniques to measure and optimize the impact of ad strategies on customer engagement and monetization.
• Collaborate with product managers to frame business problems as tractable ML problems and translate findings into product decisions.
• Shape the team’s scientific roadmap, identifying high‑impact research directions.

• Lead the research and development of ML models that personalize advertising decisions for 100M+ customers across 100k+ titles, with production deployment in mind.
• Develop deep learning architectures (multi‑task learning, embedding‑based representations) for customer behavior prediction at scale.
• Design and analyze large‑scale A/B experiments, applying causal inference techniques to measure and optimize the impact of ad strategies on customer engagement and monetization.

• Collaborate with product managers to frame business problems as tractable ML problems and translate findings into product decisions.
• Shape the team’s scientific roadmap, identifying high‑impact research directions.

The PV Ad CX team’s mission is to create the world’s most customer‑centric ad experience for video streaming. We build adaptive systems that determine when, how many, and what ads to show each customer, personalized to their viewing behavior, content context, and engagement patterns. We aspire to transform ad breaks from interruptions into moments that feel relevant and thoughtful.

• 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…