Capacity Engineering - Capacity Planning Optimization

Meta is seeking a Performance & Capacity Engineer to join the Capacity Planning and Optimization Engineering (CPOE) team to focus on site-wide performance and capacity optimization at the intersection of all Meta products and services, and all physical infrastructure (Servers, Data Centers, Network).

This role will focus on creating and optimizing capacity plans at various altitudes to balance capacity, power, and cost, in an environment of continual product introduction, directly managing billions of investment annually. We do this primarily by building software and mathematical optimization models, not manual planning. This role will be uniquely positioned to optimize these capacity plans and scalably manage exceptions at the most strategic levels with company level impact.

This is one of the most cross functional roles at the company, with the opportunity to work with a variety of engineering and business teams to power the rapid growth of Meta’s products.

This role will help to ensure optimal operation of our infrastructure from both a cost and technology perspective, with millions of servers, Gigawatts of data center capacity, and cutting edge technology including AI, Metaverse, etc. Help build one of the largest fleets, powering one of the largest internet services in the world! Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of experience in performance or software engineering and/or optimization pertinent data science or equivalent practical experience 8+ years of experience in designing and implementing models and optimization algorithms 4+ years of experience in coding/scripting languages such as Python, R, Java, C, C++, PHP 4+ years of experience with LP solvers such as Xpress or Gurobi Experience working with distributed systems at scale Experience in infrastructure operations and technical infrastructure knowledge Experience working with cross-functional teams Experience optimizing complex systems, working with large datasets, and driving business impact 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) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies