Sr. Manager, Applied Science, Prime Video Personalization & Discovery

Description 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 add‑on subscriptions such as Apple TV+, Max, 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. Key job responsibilities As the Sr. Manager, Applied Science in the Prime Video Personalization and Discovery organization, you will be responsible for optimizing the complete customer experience across all touch points throughout customers’ discovery journey. This includes building AI and optimization solutions, working with business, product, and engineering teams to deliver the optimal balance of customer delight and business outcomes. Responsibilities include direct management of senior engineers and scientists, setting vision and long‑range technical strategy, product definition, roadmap planning, driving cross‑functional execution, developing and maintaining experimentation and production services, owning ML and engineering excellence quality bar, and customer and stakeholder communication. The role also requires hiring top‑notch engineers and scientists as the organization grows. About The Team Prime Video Personalization and Discovery (PVPD) is dedicated to creating a highly personalized content discovery experience that not only delights customers but also drives short‑ and long‑term business goals. The scope includes personalized recommendations, search, marketing, and the advanced machine‑learning technology and infrastructure that underpins these experiences. The mission is to automate and enhance customer engagement through personalization, using ML and Generative AI. Basic Qualifications M.S. in Computer Science, Machine Learning, or a related field. 10+ years experience in recommendation, search, natural language processing, machine learning, or a related field. Expertise in large language models applications or demonstrated ability to develop this expertise quickly. Proven track record of leading and managing science and engineering teams in building complex, real‑time systems involving AI, ML, NLP with successful delivery to customers. Demonstrated track record of project delivery for large, cross‑functional projects with evolving requirements. Ability to take a project from requirements gathering and design to actual product launch. Excellent written and verbal technical communication with an ability to present complex technical information in a clear and concise manner to a variety of audiences. Exceptional customer relationship skills including the ability to discover the true requirements underlying feature requests, recommend alternative technical and business approaches, and lead science efforts to meet timelines with optimal solutions. Preferred Qualifications Ph.D. in Computer Science, Machine Learning, or a related field. Work with academic partners to support our in‑house talent with direct access to research and mentoring. Demonstrated track record of peer‑reviewed scientific publications that advance state‑of‑the‑art for applied science. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below; your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for 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. Learn more about our benefits at USA, WA, SEATTLE - 218,800.00 - 295,900.00 USD annually #J-18808-Ljbffr Amazon Science