From Amazon's posting. “We” and “our” refer to the employer.
Prime Video Shopping connects streamers to products tied to their favorite movies and shows, from licensed merchandise to the fashion and home goods that appear on screen. The experience is live and scaling across titles, surfaces, and countries, and science is what makes that scale possible: deciding which products belong with a given title, which moments in an episode are worth shopping, and how to turn a viewing session into a path deeper into a fandom.
We are looking for a Senior Manager of Applied Science to own this agenda, and this is a builder and manager role. You will design, build, and ship models alongside a small, senior team, and you will decide what to build in a space where the right answers are still being defined.
Current workstreams include shoppability models combining computer vision with multi-agent LLM reasoning, LLM-driven product curation across the Prime Video catalog, context-aware shopping recommendations, and the evaluation harnesses that gate what reaches customers.
Your models ship inside systems owned by partner engineering teams across Prime Video and Amazon Stores, so you will set technical direction well beyond your own organization. You will also own how we measure incrementality, since proving this work changes customer behavior matters as much as building it. The surface spans on-demand video and live sports, and you will help decide where science goes next.
Key job responsibilities
Design, build, and ship models. This is a hands-on role, and you will personally own significant parts of the science stack.
Own the science agenda for shoppable entertainment, working with product teams on what to build in a space where the problems are not yet well defined, and sequencing that work against product commitments and launch dates.
Earn trust across partner teams. Your models deploy into pipelines owned by Prime Video, Stores, and Ads engineering teams, so much of your impact comes from technical design reviews and shaping decisions that sit outside your org.
Define the quality bar for customer-facing output and build the systems that enforce it, including LLM-based evaluation, human calibration, and brand safety screening of generated content.
Own measurement, designing the experiments and causal analyses that quantify how shopping features change customer behavior, along with the metric definitions the program reports on.
Represent the science function to executive Prime Video and Stores leadership, including annual goal setting and quarterly business reviews.
Basic Qualifications
10+ years of building large-scale machine learning and AI solutions at Internet scale experience
Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
Experience building large-scale machine learning and AI solutions at Internet scale
Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track
Knowledge of data structures, algorithm design, statistics, and system design
Preferred Qualifications
10+ years of practical work applying ML to solve complex problems for large-scale applications experience
5+ years of hands-on work in big data, machine learning and predictive modeling experience
5+ years of people management experience
PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
Experience in people management
Experience with Java, C++, or other programming language, as well as with R, MATLAB, Python, or an equivalent scripting language
Equal Opportunity
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 https://amazon.jobs/content/en/how-we-hire/accommodations 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 https://amazon.jobs/en/benefits.
USA, WA, SEATTLE - 218,800.00 - 295,900.00 USD annually
About this listing
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