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

Amazon Amazon · Big Tech · Seattle, WA · Project/Program/Product Management--Technical

Principal Product Manager for Prime Video Personalization and Discovery, focusing on Monetization Strategy. This role involves defining product vision, strategy, and roadmap for ML-powered features, including recommendation systems. Responsibilities include translating business problems into algorithmic objectives, collaborating with applied scientists and ML engineers, defining metrics, leading A/B testing, and communicating complex concepts to leadership. The role requires experience managing and deploying ML products and understanding the model lifecycle.

What you'd actually do

  1. Own the roadmap and strategy for personalization products, including recommendation systems and ML/science-based models.
  2. Collaborate with applied scientists and ML engineers to translate business problems into model requirements and convert them into clear algorithmic objectives, metrics, and guardrails.
  3. 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.
  4. Lead A/B testing strategy and experimentation to validate algorithmic improvements and inform roadmap decisions.
  5. Partner with stakeholder teams to understand business needs and translate them into technical specifications and prioritized work.

Skills

Required

  • 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
  • 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.

Nice to have

  • 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.

What the JD emphasized

  • ML-powered features at scale
  • deliver broadly adopted technology products or services
  • deliver at high scale
  • customer value and measurable business outcomes
  • complex algorithmic capabilities
  • model requirements
  • algorithmic objectives
  • model lifecycle
  • data readiness
  • model evaluation frameworks
  • deploying ML products
  • Large Language Model fundamentals
  • architecture, training/inference lifecycles
  • optimization of model execution
  • modern ML techniques
  • Agentic AIs

Other signals

  • ML-powered features at scale
  • recommendation systems
  • ML/science-based models
  • algorithmic objectives
  • ML products
  • model lifecycle
  • model evaluation frameworks
  • modern ML techniques
  • Agentic AIs