Meta is seeking a Director, Hardware Supply Chain Planning to serve as a senior individual contributor for server rack and component planning across Meta's infrastructure supply chain. This is an individual contributor role with no people management responsibilities. This role owns the technical direction of how we plan, constrain, and commit tens of billions of dollars of server rack and component supply annually, balancing capacity, flexibility, supply capability, and cost, from base components to finished racks, in an environment of continual product introduction. We do this primarily by building software and mathematical optimization models, not manual planning. The person in this role is the senior technical lead whom cross-functional leadership trusts and from whom the planning team takes technical direction. They set the methodology, arbitrate the hard modeling and prioritization calls, steer supply feasibility runs and significant plan revisions end to end, and personally carry out the analyses that leadership relies on to make multi-billion dollar commitments. Influence here comes from technical credibility and judgment rather than reporting lines: this role routinely aligns Director- and VP-level partners across Infra, Sourcing, Finance, and Hardware Engineering on a single plan of record. This is a high-ambiguity, high-leverage role at the center of Meta's AI and data center scaling strategy: millions of servers, gigawatts of capacity, and current-generation silicon. If you are passionate about optimizing complex systems, working with large datasets and supply chains, and driving company-level business impact as a technologist rather than a manager, we encourage you to apply.

Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Industrial Engineering, Operations Research, a relevant technical field, or equivalent practical experience 12+ years of experience in supply chain management (planning, manufacturing, operations, inventory, etc.), including hardware or other capital-intensive, long-lead-time supply chains.8+ years of experience in performance or software engineering and/or optimization of data science 10+ years of experience designing and implementing models and optimization algorithms that are used to make production business decisions, not just to inform analysis 10+ years of experience in coding/scripting languages such as Python, R, Java, C, C++, PHP, and with large-scale data platforms (SQL, distributed compute, pipeline orchestration) Experience setting technical direction for large, cross-organizational programs as an individual contributor, driving outcomes and alignment through influence rather than reporting lines Experience owning a technical domain end to end at company scale, including being the escalation point for the hardest decisions in that domain Experience working with distributed systems at scale Experience in supply chain planning optimization Experience in infrastructure operations and technical infrastructure knowledge, including server, rack, and component architecture Experience in communicating technical recommendations to and building consensus with director- and VP-level cross-functional partners Experience defining approaches and driving decisions in situations with incomplete information or evolving requirements Track record of success in planning for a complex supply chain environment M.S. or Ph.D. degree in Computer Science, Mathematics, Operations Research, Supply Chain Analytics, or other technical field Experience being the recognized go-to technical expert in a domain where the correct answer is genuinely contested Experience interfacing with internal and external partners in an entrepreneurial and cross-functional environment, requiring latitude for independent judgment while coordinating people and technical resources Experience transforming business systems, models, and achieving results relative to goals. Experience identifying opportunities to improve established processes and delivering measurable results through novel approaches Experience with data center, server, or AI hardware supply chains, including silicon, memory, storage, or network component constraints