Senior Applied Scientist , Prime Video Ads

Senior Applied Scientist , Prime Video Ads Job ID: 10422112 | Amazon.com Services LLC 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 in the process of building the science foundation to make our ad experience the most customer‑centric in the industry. Unlike traditional digital advertising where clicks and conversions provide direct feedback, streaming presents unique scientific challenges. Indirect signals, heterogeneous customer responses, and the need to balance monetization with long‑term engagement, all at massive scale. Key Job Responsibilities 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. Partner with engineering to ensure models meet production latency and scalability requirements. 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. A Day In The Life 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. Partner with engineering to ensure models meet production latency and scalability requirements. 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. 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 large‑scale distributed systems such as Hadoop, Spark etc. Experience working with PyTorch or JAX software, or expertise in Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution. Benefits Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and optional Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Salary Base salary range varies by location: USA, NY, New York: $183,800.00 – $248,700.00 USD annually USA, VA, Arlington: $167,100.00 – $226,100.00 USD annually USA, WA, SEATTLE: $167,100.00 – $226,100.00 USD annually Amazon package includes sign‑on payments and restricted stock units (RSUs). Final compensation is determined based on factors including experience, qualifications, and location. Learn more about our benefits at Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. #J-18808-Ljbffr