About the job
Prime Video is looking for an experienced Principal Product Manager to own the vision, strategy, and roadmap for the Monetization Strategy that is a key component of our Personalization and Discovery experiences. You will operate at the intersection of machine learning, customer experience, and business strategy, leading fast-paced, high-impact projects and partnering with experts in data science, ML engineering, and customer experience to ship ML-powered features at scale.
Responsibilities
Own the roadmap and strategy for personalization products, including recommendation systems and ML/science-based models.
Collaborate with applied scientists and ML engineers to translate business problems into model requirements and convert them into clear algorithmic objectives, metrics, and guardrails.
Define, track, and analyze key metrics to measure recommendation quality, customer outcomes, and business impact; analyze user behavior data to identify opportunities to improve personalization.
Lead A/B testing strategy and experimentation to validate algorithmic improvements and inform roadmap decisions.
Partner with stakeholder teams to understand business needs and translate them into technical specifications and prioritized work.
Communicate complex technical and algorithmic concepts clearly to senior leadership and cross-functional partners.
Balance trade-offs between model complexity, latency, scalability, and business value to ensure robust, production-ready solutions.
Qualifications
Minimum
8+ years of technical product or program management experience
Experience with feature delivery and tradeoffs of a product
6+ years of end to end product delivery experience
Experience owning/driving roadmap strategy and definition
Experience leading engineering discussions around technology decisions and strategy related to a product
Bachelor's degree
Experience managing and deploying ML products
Experience leading and influencing your team or organization, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
Background in an applied science, engineering, or quantitative field, with a solid understanding of the model lifecycle, data readiness, and model evaluation frameworks.
Preferred
Experience in project management methodologies, business analysis, or process improvement
Bachelor's degree in a quantitative/technical field such as computer science, engineering, statistics
Experience as a strong leader who can prioritize well, communicate clearly and effectively influence across cross-functional teams
Experience working with and influencing senior level stakeholders
Experience in content discovery, e-commerce, search, or recommendation systems
Knowledge of modern ML techniques (deep learning, NLP, LLM, Agentic AIs) and their practical trade-offs.