Meta is seeking a Performance & Capacity Engineer to join the Capacity Engineering & Analysis 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). You will build and optimize infrastructure capacity planning processes and tools covering all of Meta, in one of our largest transformations of how we plan and manage infrastructure capacity. You will be in a highly cross-functional role, with the opportunity to work with a variety of engineering and business teams at the intersection of all Meta products and services (Facebook, Instagram, WhatsApp, etc), all physical infrastructure (Servers, Data Centers, Network), and product business goals (AI, Metaverse, etc). You will optimize capacity plans that inform strategic infrastructure and product decisions at the executive level, as well as providing execution guidance for infrastructure and product teams. To do this, you will partner across technical and business orgs to design the right solutions and lead engineers to build effective technical and process solutions to transform Meta's capacity planning process to be software driven, highly flexible, agile, and ROI Driven. You will connect business strategy with software-driven modeling of detailed service, platform, and infrastructure considerations for executable plans.
Responsibilities
Own both technical as well as business outcomes for capacity planning for all of Meta: all software products/services and plans for how to scale server and data center resources most efficiently Build automated, scalable data and analytics solutions by developing advanced automation, mathematical optimization, and/or AI models Use the tools you build to own the business outcomes: develop and analyze variety of business and technical scenarios to inform executive decision-making around infrastructure/product, up to the CxO level Design and help build software systems to build scalable, reliable planning systems to connect business strategy with detailed technical execution including regional and temporal bin-packing, optimal service placement, traffic shifts and service migrations, efficient hardware refresh, etc Partner across the engineering technical landscape to optimize at the intersection of hardware, infrastructure, and software. Work closely with software service owners, Production Engineering, Server Hardware Engineering, Server Supply Chain, Network Engineering, Data Center Design, Operations, and Planning teams to identify efficient ways to scale infrastructure and place our services Effectively lead company-wide Capacity Planning business processes across technical and non technical contributors Partner with Finance to balance cost efficiency with technical and product considerations Greenfield work: Work cross-functionally to define problem statements, collect data, build software-driven models and make recommendations to drive change and optimization at the company level
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of experience in any coding language and designing software systems, OR 4+ years experience with a PhD 8+ years of experience in capacity, performance, software, or reliability engineering, OR 4+ years experience with a PhD Experience navigating ambiguous problem spaces and ramping up on new technical and business domains to deliver results 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 Practical experience and demonstrated success in Capacity Planning for a major private or public cloud Experience with planning for large-scale technical infrastructure and distributed systems Experience working with variety of technical and business teams Experience with mathematical optimization Experience and interest in building "Zero to One" - building systems and process from scratch with ambiguous requirements and goals MS or PhD in Computer Science, Operations Research, or other technical field