Principal Product Manager Tech, Prime Video Personalization & Discovery

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

Principal Product Manager Tech for Prime Video Personalization & Discovery, focusing on owning the vision, strategy, and roadmap for core recommendation systems and ML models. The role involves translating business problems into model requirements, defining metrics, leading A/B testing, and making trade-off decisions for ML-powered features at scale, with a strong emphasis on customer value and business outcomes.

What you'd actually do

  1. Own the strategy and roadmap for personalization products, including recommendation systems and ML 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 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

  • 2+ years of end to end product delivery experience
  • 8+ years of technical product or program management experience
  • Bachelor's degree
  • Experience with feature delivery and tradeoffs of a product
  • Experience owning/driving roadmap strategy and definition
  • Experience leading engineering discussions around technology decisions and strategy related to a product
  • Experience technical product management

Nice to have

  • Experience working directly with Engineers on product enhancements
  • Experience in project management methodologies, business analysis, or process improvement
  • Experience owning data-centric products
  • Working knowledge of machine learning algorithms
  • Prior machine learning experience, familiarity with statistical data analytics techniques
  • Knowledge of modern ML techniques (deep learning, NLP, LLM, Agentic AI) and their practical trade-offs
  • Fluency in technology alternatives with ability to weigh pros and cons of different technical approaches
  • Strong leadership skills with ability to influence cross-functional teams and drive alignment among diverse stakeholders
  • Experience working with senior-level stakeholders and communicating complex technical concepts to executive leadership
  • Experience in project management methodologies, business analysis, or process improvement

What the JD emphasized

  • ML-powered features at scale
  • customer value and measurable business outcomes
  • ML lifecycle
  • algorithmic objectives, metrics, and guardrails
  • model complexity, latency, scalability, and business value

Other signals

  • ML-powered features at scale
  • recommendation systems
  • customer value and measurable business outcomes
  • ML lifecycle
  • algorithmic objectives, metrics, and guardrails
  • A/B testing strategy and experimentation
  • model complexity, latency, scalability, and business value