About the job
The Prime Video Personalization & Discovery team is seeking a Senior Product Manager - Tech with Personalization to own the vision, strategy, and roadmap for the core recommendations that power 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 that ship ML-powered features at scale.
Responsibilities
Own the strategy and roadmap for personalization products, including recommendation systems and ML 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 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; Make and own trade-off decisions between model complexity, latency, scalability, and business value, ensuring robust, production-ready solutions that deliver customer value.
Qualifications
Minimum
5+ years of technical product or program management experience; 3+ years of end to end product delivery experience; Bachelor's degree; Experience contributing to engineering discussions around technology decisions and strategy related to a product; Experience with feature delivery and tradeoffs of a product; Experience owning/driving roadmap strategy and definition; Experience managing technical products or online services; Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning; 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 building and driving adoption of new tools; Knowledge of machine learning approaches and algorithms; Experience influencing multiple stakeholders and leading cross functional teams across geographies and business units