AI Product Manager, Catalog and Content Understanding

Netflix•Los Gatos, CA

12d•$400,000 - $640,000

About The Position

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. Our unique culture drives our approach to innovation, and our small, focused product teams empower individuals to make a big impact. We strongly believe that a diversity of experiences and backgrounds leads to a better environment for our employees and better products for our customers. The Team The Content Platform Operations & Publishing (CPOP) team sits at the intersection of AI and machine learning, the consumer experience, and the Netflix Studio. We build the internal tools that power how Netflix understands, organizes, and manages its content catalog — from metadata and asset management to the systems that make sense of what's actually in our content. Our products impact both the teams who operate the catalog, the linguists/editors/executives who rely on accurate, structured content understanding to do their jobs and ultimately impacts how members find context and meaning to the content they watch on Netflix. We are seeking a Product Manager with a strong understanding of machine learning and a passion for AI innovation to own the strategy and product vision for our internal catalog management and content understanding tools. In this role, you will: Define and drive the AI strategy for the products that manage Netflix's content catalog, from metadata systems to content understanding pipelines. Own the product vision for how AI and machine learning models are applied to structure, enrich, and make sense of an ever-growing and increasingly complex content catalog. Collaborate with cross-functional teams to build intelligent systems that automate and improve catalog operations. Identify and implement novel AI-driven solutions to complex challenges in content understanding, cataloging, and asset management, keeping our internal tooling at the cutting edge. Partner with researchers, engineers, and internal stakeholders to translate advances in AI/ML into scalable, user-centric internal products. If you thrive at the intersection of AI technology and content, and are excited to shape how Netflix understands and manages its catalog through intelligent tooling, we'd love to hear from you!

Requirements

7+ years of product management experience with a proven record of prioritizing and successfully launching impactful products or platforms.
Intermediate or advanced knowledge of machine learning techniques and evaluation best practices.
Ability to mobilize an organization toward a common goal and build strong relationships across functions.
Experience leading end-to-end products that incorporate ML/AI, including launching LLM integrations and customizing underlying models.
Experience with the ML lifecycle (data collection and labeling, model evaluation, etc.).
Applied experience using data to inform priorities and evaluate impact.
Excellent written and verbal communication skills.

Nice To Haves

Experience building internal tools, platforms for internal partners, or B2B enterprise products is a plus.
Experience with content metadata, catalog systems, or content understanding (e.g., NLP, LLM) is a plus.

Responsibilities

Own the strategic roadmap for AI-driven catalog management and content understanding tools — from concept through validation, shipping, measurement, and iteration. Author strategy memos and presentations to represent this vision to senior executives.
Lead the incubation and system design of new ML/AI capabilities for end user challenges and use cases, from idea to production, in partnership with applied researchers, data scientists, and engineers.
Discover unmet needs from the teams operating the content catalog, distilling them into a product roadmap that drives measurable business impact.
Communicate your AI strategy and vision broadly across the organization, translating technical and complex concepts for non-technical audiences.
Use rigorous, hypothesis-driven analysis and ML/AI evaluation skills to set priorities, build business cases, and measure impact.