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Meta is seeking a Director of Product Management for AI Platforms and Infrastructure to own the end-to-end product strategy for Meta's recommendation systems infrastructure. This role spans model authoring, training, inference, and the developer experience connecting them across Monetization, Instagram, and Facebook.
You will define how ML engineers across Meta's product surfaces build, train, and ship recommendation models, directly impacting product quality and velocity. Key responsibilities include:
• Own product strategy across four core pillars: MLE productivity (reducing friction in ML workflows), research-to-production velocity (shortening experimentation-to-launch cycles), quality and reliability (robust, scalable tooling), and foundational infrastructure (data, developer experience, training, inference capabilities).
• Drive MLE productivity by identifying high-friction points in ML workflows and building tooling to eliminate them.
• Partner with engineering and research leaders to translate infrastructure capabilities into measurable improvements in model quality, training efficiency, and launch reliability.
• Build and lead a team of product managers, establishing clear charters across the ML stack and fostering an environment where PMs develop conviction and ship independently.
• Sequence investments across a broad portfolio, balancing near-term pain points against foundational infrastructure bets with long-term compounding value.
• Establish alignment across AI Infra, recommendation teams, and product surfaces with competing infrastructure priorities.
• Define and instrument metrics demonstrating whether MLEs move faster, models launch more reliably, and infrastructure investments deliver ROI.
• Lead teams through ideation, technical development, and product launch of innovative solutions.
• Build consensus on strategies and priorities across the company, driving product execution.
• Integrate usability studies, research, and market analysis into product requirements.
• Manage multiple products and priorities, scale teams, and ensure organizational health through clear, measurable goals.
Required: 12+ years in Product Management or equivalent; 12+ years collaborating with engineering, design, and research teams; 8+ years hiring, managing, and developing individual contributors and senior ICs; strong analytical and critical thinking leadership; excellent written and verbal communication; BA/BS in Computer Science or related field.
Preferred: Deep familiarity with ML systems (training infrastructure, model serving, feature engineering, ML data pipelines at scale); experience building developer tools/platforms for ML engineers, data scientists, or researchers; understanding of recommendation systems and ranking/retrieval/personalization tradeoffs; track record managing infrastructure products where the user is an internal engineer.
