About the TeamRoku's Recommendations team powers nearly all Roku-controlled UI surfaces, presenting content, apps, and offers through personalized browse pages, carousels, rows, and destination experiences across 100+ surfaces. The system matches over 100M viewers to millions of entertainment entities daily, optimizing for user engagement, monetization, and long-term platform health.
About the RoleWe are looking for a Senior Product Manager to own and drive critical product areas within Recommendations. In this role, you will be responsible for defining product strategy, leading experiments, and delivering measurable outcomes that drive viewer engagement KPIs and business model outcomes (for ad-supported, subscription, and TVOD/PVOD), through the ML/AI recommendations ecosystem.
This is a high-ownership, high-visibility role. You will operate across multiple surfaces and partner closely with engineering, UX, data science, content, business, and cross-functional PMs to shape how Roku's recommendations platform serves users and the business.
For New York Only - The estimated annual salary for this position is between $195,000 - $303,000 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.
What You'll Be Doing- Define and own the product strategy and roadmap for your area within Platform Recommendations, with a focus on maximizing user engagement and business value across all monetization models
- Identify unique problem spaces across surfaces and develop strategic recommendations backed by data and analysis
- Drive material outcomes from strategic themes: Drive material outcomes from strategic themes through deep, independent analysis, quantified impact, coherent recommendations, and leadership-ready proposals
- Articulate customer and business problems clearly: Articulate customer and business problems clearly, evaluate options and trade-offs, and develop sequenced roadmaps that move the ball forward strategically
- Lead KPI definition and defense: propose clear primary decision metrics and supporting metrics for every initiative, especially in ambiguous domains where north-star KPIs are not easily defined
- Own experiment design end-to-end: define test contracts and hold the line on experimental rigor
- Drive experiments to decisions: ensure every test is tied to a concrete decision or roadmap change, and prevent KPI drift by proactively aligning stakeholders
- Move fast and demonstrate extreme ownership of outcomes: actively track, unblock, and push for value, and propose concrete options when faced with trade-offs
- Maintain 100% lockstep with partners: Maintain 100% lockstep with partners in ML Research and Engineering, Merchandising, and Analytics with detail orientation and ensure alignment on strategy, outcomes and requirements/timelines
- Communicate with clarity and conciseness: Communicate with clarity and conciseness, with high signal-to-noise in written documents, messaging, presentations and verbal discussions
- Proactively keep stakeholders informed: Proactively keep stakeholders informed of progress, risks, and blockers with specific impacts, options and recommended paths
We're Excited If You Have- 7+ years of product management experience, ideally in recommendations, personalization, search/discovery, or ML/AI-driven product areas
- Strong analytical rigor: comfort with experiment design, A/B testing, statistical significance, and metric frameworks. Ability to define, defend, and prevent drift on KPIs
- Proven ownership and bias to action: track record of driving complex, ambiguous initiatives end-to-end - from problem framing through strategy to shipped outcomes. You escalate early, propose alternatives, and don't let work stall
- Technical depth: experience working closely with ML engineers and data scientists on ranking, optimization, and signal-based systems. Ability to engage meaningfully in technical discussions about model performance, feature engineering, and system architecture
- Excellent cross-functional leadership: demonstrated ability to influence and drive alignment across engineering, data science, design, business, and content teams without direct authority
- Outcome-oriented experimentation mindset: experience designing and running experiments that drive real product and business decisions
- Clear, concise communicator: strong written and verbal skills; ability to present strategy, trade-offs, and recommendations to executive leadership
- Experience in streaming, media, entertainment, or large-scale content platforms
- Familiarity with recommendation systems, content ranking, collaborative filtering, or personalization at scale (100M+ users)
- Experience with GenAI/LLM applications in product discovery, content understanding, or signal generation
- Experience operating across multiple product surfaces (TV, mobile, web) with different user behaviors and constraints
- BS/MS in a quantitative field (engineering, CS, mathematics); MBA a plus
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