Server Demand Planner, Engineering

Description

Meta is seeking a Staff-level Server Demand Planner to join the Engineering team, where operations research and infrastructure planning intersect at global scale. In this role, you will apply advanced quantitative methods and optimization techniques to forecast server demand, model capacity requirements, and drive strategic planning decisions that ensure Meta's data center infrastructure can support billions of users across its family of apps and services. You will own end-to-end demand planning models, translate complex supply-demand signals into actionable capacity roadmaps, and partner with hardware, software, and finance stakeholders to align infrastructure investment with product growth trajectories.

Responsibilities

Develop and own large-scale server demand forecasting models using operations research techniques such as time-series analysis, stochastic optimization, and simulation to project infrastructure needs across multi-year planning horizons Build and maintain capacity planning frameworks that translate product growth signals, efficiency improvements, and hardware generation transitions into server procurement and deployment recommendations Identify and resolve demand-supply imbalances by analyzing fleet utilization data, workload trends, and capacity headroom across Meta's global data center footprint Design and implement optimization models to improve server allocation efficiency, reduce stranded capacity, and minimize infrastructure costs while meeting reliability and performance targets Partner with hardware engineering, data center operations, and finance teams to align server demand plans with procurement lead times, capital budgets, and deployment schedules Establish and maintain dashboards, alerting systems, and reporting pipelines that provide real-time visibility into capacity health, forecast accuracy, and planning KPIs Lead retrospectives on forecast accuracy and demand model performance, identifying systematic biases and implementing improvements to reduce mean absolute error across planning cycles Drive cross-functional alignment on capacity planning assumptions, scenario analyses, and risk assessments to support executive-level infrastructure investment decisions Mentor other engineers and analysts on operations research methodologies, demand modeling best practices, and capacity planning workflows Contribute to the evolution of capacity planning tooling and automation, reducing manual planning effort and improving the scalability of the demand planning process

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of experience in capacity planning, demand forecasting, operations research, or supply chain optimization within large-scale infrastructure or technology environments Experience developing and deploying quantitative forecasting or optimization models (e.g., time-series forecasting, linear programming, stochastic optimization, simulation) applied to infrastructure or hardware planning problems Experience working with large-scale data pipelines and analytical tools to extract, transform, and analyze fleet utilization, workload, and demand signals Experience driving cross-functional planning processes involving hardware engineering, finance, and data center operations stakeholders Experience communicating complex quantitative analyses and capacity planning recommendations to technical and non-technical audiences through written documents and presentations Track record of building or improving capacity planning tooling that reduced planning cycle time or improved forecast accuracy at organizational scale Experience applying machine learning techniques (e.g., gradient boosting, neural networks) to improve demand forecast accuracy in infrastructure planning contexts Experience with server or data center capacity planning at hyperscale, including familiarity with hardware generation transitions, procurement lead times, and fleet lifecycle management Proficiency in Python, SQL, or similar languages for building and automating demand forecasting and optimization workflows

Compensation: $184,000/year to $257,000/year + bonus + equity + benefits