Senior Applied Scientist , Prime Video Ads

Overview 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 Prime membership, can rent or buy titles via the Prime Video Store and enjoy additional free content with ads. 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. Address science challenges across the full ML lifecycle, from exploratory research and offline modeling to online experimentation and production deployment. Understand heterogeneous customer responses and predict variation to inform real‑time advertising decisions. Infer customer preferences and tolerance from indirect behavioral signals in the absence of clicks and conversions. Build systems that adapt ad load, placement, and content to individual viewers at scale. Measure, attribute, and optimize small signal effects requiring rigorous experimental design and causal methodologies. Navigate competing objectives—revenue, engagement, retention, and advertiser value—using principled frameworks for sustainable outcomes. 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 with machine learning and large language model fundamentals—including architecture, training/inference lifecycles, and optimization of model execution. Compensation & Benefits 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, dental, vision, prescription, basic life & AD&D insurance, 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. Learn more at 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 Equal Opportunity Statement 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, please visit for more information. Company Amazon.com Services LLC Job ID: A10422112 #J-18808-Ljbffr Prime Video & Amazon MGM Studios