Product Management, Director - AI Platforms and Infra

**Summary:** This team is the part of AI Platforms and Infra that powers the tooling and systems behind recommendation models across Monetization, Instagram, and Facebook. The mission is simple but high-impact: help ML engineers move fast — taking an idea from authoring to training to production inference with high confidence.You will own the product strategy across four areas that define how quickly and reliably Meta ships recommendation models:MLE productivity — reduce friction in ML workflows and make iteration meaningfully fasterResearch-to-production velocity — shorten the cycle time from experimentation to reliable launchesQuality and reliability — build tooling and systems that are robust, scalable, and trustworthy across the ML stackFoundational infrastructure — deliver capabilities spanning data, developer experience, training, and inference that unlock new recommendation quality **Required Skills:** Product Management, Director - AI Platforms and Infra Responsibilities: 1. Own the end-to-end product strategy for Meta's recommendation systems infrastructure — spanning model authoring, training, inference, and the developer experience that ties them together 2. Define how ML engineers across Monetization, Instagram, and Facebook build, train, and ship recommendation models — your decisions directly affect the quality and velocity of these products Drive MLE productivity by identifying the highest-friction points in ML workflows and building tooling that removes them 3. Partner with engineering and research leaders to translate infrastructure capabilities into measurable improvements in model quality, training efficiency, and launch reliability 4. Build and lead a team of product managers, setting clear charters across the ML stack and creating an environment where PMs develop conviction and ship independently 5. Sequence investments across a broad portfolio — making deliberate tradeoffs between near-term MLE pain points and foundational infrastructure bets that compound over time 6. Establish alignment across AI Infra, recommendation teams, and product surfaces whose competing needs shape infrastructure priorities 7. Define and instrument the metrics that tell you whether MLEs are actually moving faster, models are launching more reliably, and infrastructure investments are paying off 8. Lead a team through the ideation, technical development, and launch of innovative products 9. Establish shared vision across the company by building consensus on strategies and priorities leading to product execution 10. Drive product development with a team of world-class engineers and designers Integrate usability studies, research and market analysis into product requirements to enhance user satisfaction 11. Define and analyze metrics that inform the success of products Understand Meta’s strategic and competitive position and deliver products that are recognized as best in the industry 12. Maximize efficiency in a constantly evolving environment where the process is fluid and creative solutions are the norm 13. Attract, build, manage, and develop a talented team of product leaders with a broad range of experiences, perspectives, approaches, and backgrounds 14. Manage multiple products and priorities, scale teams, and ensure org is effective, healthy and set up for success by establishing clear and measurable goals **Minimum Qualifications:** Minimum Qualifications: 15. 12+ years of experience in Product Management and/or equivalent relevant experience 16. 12+ years of experience working collaboratively with engineering, design and user research teams 17. 8+ years of experience hiring, managing, and developing both individual contributors and senior individual contributors 18. Critical thinking/analytical leadership experience 19. Strong written and verbal communication - ability to distill complex technical topics into clear documents for executive audiences **Preferred Qualifications:** Preferred Qualifications: 20. Deep familiarity with ML systems — training infrastructure, model serving, feature engineering, or ML data pipelines at scale 21. Understanding of recommendation systems and the tradeoffs in ranking, retrieval, and personalization at scale **Public Compensation:** $249,000/year to $323,000/year + bonus + equity + benefits **Industry:** Internet **Equal Opportunity:** Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.