Performance & Capacity Engineer - Planning Optimization

About the Role

Meta is seeking a Performance & Capacity Engineer to join the Capacity Engineering & Analysis team, focusing on site-wide performance and capacity optimization. This role operates at the intersection of all Meta products and services, and all physical infrastructure including Servers, Data Centers, and Network. You will be responsible for creating and optimizing global and regional capacity plans across various levels to balance service, infrastructure, financial, and business constraints, directly managing billions of dollars in investment annually.

This position covers all Meta products, platforms, and physical hardware, from tactical near-term granular optimized plans to strategic company-level impacts at the CxO level. The primary approach involves building software and mathematical optimization models, rather than manual planning. You will achieve these goals by leveraging a combination of capacity/performance engineering and/or operations research/data science skills. This highly cross-functional role offers the opportunity to collaborate with diverse engineering and business teams, powering Meta’s rapid growth. You will help ensure optimal operation of our infrastructure from both a cost and technology perspective, overseeing millions of servers, Gigawatts of data center capacity, and cutting-edge technology, including some of the world's largest AI infrastructure builds. Join us in building one of the largest fleets, powering one of the largest internet services globally!

Responsibilities of a Performance & Capacity Engineer - Planning Optimization:

• Own both technical and business outcomes for capacity planning across all of Meta, including all software products/services and strategies for efficiently scaling server and data center resources.
• Develop automated, scalable data and analytics solutions by building state-of-the-art automation, mathematical optimization, and/or AI models using Meta’s unparalleled data infrastructure.
• Utilize the tools you build to drive business outcomes: develop and analyze various business and technical scenarios to inform executive decision-making on infrastructure/product, up to the CxO level.
• Collaborate 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 optimal methods for scaling infrastructure and service placement.
• Partner with Finance to achieve a balance between cost efficiency and technical and product considerations.
• Undertake Greenfield work: define problem statements, collect data, build analytical models, and make recommendations cross-functionally to drive strategic change and optimization.
• Identify capacity-related issues proactively and collaborate with technical and business teams to define and implement solutions.

Minimum Qualifications:

• Currently holds, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or possesses equivalent practical experience. Degree must be completed prior to joining Meta.
• Minimum of 4 years of experience working with distributed systems at scale.
• Proficient in any coding language and experienced in designing software systems.
• Demonstrated desire to learn about capacity planning and optimization.
• Experience managing ambiguity and learning/applying new business and technical concepts.

Preferred Qualifications:

• MS or PhD in Computer Science, Operations Research, or another technical field.
• Experience with mathematical optimization.
• Practical experience and demonstrated success in performance or capacity engineering.
• Experience with planning and analytics.
• Direct experience in capacity planning for a major private or public cloud.

Key skills/competency

• Capacity Planning
• Performance Engineering
• Mathematical Optimization
• Distributed Systems
• Data Science
• AI Models
• Infrastructure Scaling
• Software Design
• Business Acumen
• Cross-functional Collaboration