Principal Product Manager - Tech, Personalization and Monetization, Prime Video Personalization & Discovery

Amazon
Seattle, Washington, USA2026-03-05ONSITE

About the job

We are 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 management experience.

6+ years of end to end product delivery experience

Bachelor's degree

Experience with feature delivery and tradeoffs of a product

Experience owning/driving roadmap strategy and definition

Experience managing consumer-facing products where ML directly impacts user experience and engagement.

Experience leading science and technology discussions and influencing strategy for ML- or science-driven products.

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 content discovery, e-commerce, search, or recommendation systems

Knowledge of modern ML techniques (deep learning, NLP, LLM, Agentic AIs) and their practical trade-offs.

Strong leadership skills with ability to influence cross-functional teams

Experience working with senior-level stakeholders

Experience in project management methodologies, business analysis, or process improvement