Meta
Product Manager
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Product Manager - Product Intelligence AI / ML Team
We are looking for a Product Manager to work on the Product Intelligence AI / ML team. This role is broadly responsible for driving product strategy, goal setting, and execution for the ML Modeling track of Product Intelligence and Catalog Metadata. The person in this role will serve as a product and technical leader for a deep-tech, AI-first area.
Catalog is a key part of the broader Ads organization, primarily responsible for the end-to-end lifecycle of high-quality product and website data. Our core mission is to acquire, enrich, and deploy this data across Meta’s ecosystem to enable delightfully relevant, automated ads experiences at scale. Currently, Catalog-powered Ads represent some of the highest-performing ad formats at Meta, contributing a significant portion of total Meta revenue. Beyond the core Ads business, Catalog acts as a vital foundational layer for several emerging Meta initiatives. These include next-generation commerce experiences such as Shop Everything, Meta AI Shopping, and Business Agents.
Responsibilities
- Drive product vision, strategy, and roadmap for the ML Modeling track — Product Content Understanding, Product Embedding & Retrieval, and Metadata Extraction.
- Identify the highest-leverage modeling and data levers with engineering, and prioritize execution towards high quality as measured by defined benchmarks.
- Understand Meta’s strategic and competitive position in product understanding and visual search, and deliver capabilities recognized as best in the industry.
- Incorporate data, research, benchmarking, and market analysis to inform product strategy and roadmap.
- Expand utilization of Catalog/Product Intelligence capabilities across Meta use cases (Shop Everything, ranking, retrieval, MSL, and others), converting partner demand into platform primitives rather than bespoke builds.
- Own intake, prioritization, and communication for partner asks, and operationalize cross-organizational working models with deep-tech partners (MGenAI, PCA, MSL).
- Drive product development with a team of ML engineers and designers, while maintaining team health.
- Work closely with cross-functional teams to define product requirements, coordinate resources from other groups (design, research, legal, etc.), and guide the team through key milestones.
- Operate independently, think strategically, and communicate effectively — including to leadership audiences — to drive successful outcomes.
- Define and analyze the metrics and benchmarks that inform the success of these capabilities (e.g., exact match, precision/recall, latency, coverage), and identify and track key performance metrics.
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Minimum Qualifications
- 2+ years in Product Management working collaboratively with engineering, design, and user research teams.
- Experience partnering with ML/research engineering teams and translating model capability into shipped product surfaces or APIs.
- Experience working in the Advertising, e-Commerce, or AI/ML industry on data and machine learning-led products such as data acquisition, enrichment, content understanding, embeddings, retrieval, or ranking.
- Experience navigating the full product life-cycle, integrating customer feedback into product requirements, driving prioritization, and pre/post-launch execution.
- Critical thinking and analytical leadership experience, including defining metrics and quality benchmarks.
- Experience communicating with and presenting to leadership and technical audiences.
- Experience building and shipping high-quality work and achieving high reliability.
- AI native PM with demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements).
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Preferred Qualifications
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements).
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews).
- Experience with multimodal models, embeddings, and retrieval systems, or visual search / product recognition.
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies.
- Experience working on Catalog or product-data related products in e-commerce or advertising.
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