Performance & Capacity Engineering - Capacity Planning Optimization
About the role
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.
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.
Responsibilities
- Own infrastructure capacity planning for Meta: including Servers, Data Centers, Network
- Design, implement and launch software systems to improve capacity planning efficiency and quality, partnering with software engineers
- Contribute to end to end capacity planning processes, methodologies, and data to deliver executable and optimized plans
- Manage and resolve critical escalations and exceptions in all areas of the capacity planning
- Build linear programming models to perform simulation and optimization studies of demand and supply projections, scenario planning, and feasibility analysis while balancing various constraints
- Work cross-functionally to define problem statements, collect data, build analytical models and make recommendations to drive change and optimization at the most strategic levels
- Partner across Infra: such as platform teams, operations, networking planning, data center planning as well as Product and Finance teams to find the most optimal ways to scale our Infrastructure
- Effectively navigate complex tradeoffs and relationships to balance solving for team, cross-functional partner / stakeholders, and Meta company priorities
Qualifications
The minimum qualifications for this role include a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience, as well as:
- 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
Preferred Qualifications
- 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
Pay
The salary for this role is $184,000/year to $257,000/year, plus bonus, equity, and benefits. Individual compensation is determined by skills, qualifications, experience, and location.