Research Scientist, Infrastructure Modeling and Reliability
Meta· Data Center Strategy
Menlo Park, CA$271k - $347kFull-timePosted 2mo ago
About the role
Meta seeks a Research Scientist or Applied Scientist to define and build modeling approaches for power utilization across Meta’s infrastructure. The role focuses on developing statistical and machine learning models to monitor power consumption, forecast peak demand, quantify uncertainty, and inform how to maximize usable power within reliability constraints across large-scale infrastructure.
Responsibilities
- Define the scientific and technical strategy for modeling power consumption, peak risk, and reliability tradeoffs across large-scale infrastructure systems.
- Develop statistical, machine learning, and/or optimization models that forecast power demand, estimate peak distributions, quantify uncertainty, and support operational decision-making.
- Build approaches that reason about high-dimensional signals, correlated demand, failure-domain constraints, reserve margins, and reliability targets.
- Partner with engineering, capacity planning, data center, energy, hardware, operations, and finance teams to translate model outputs into infrastructure planning and utilization decisions.
- Establish evaluation frameworks, backtesting methods, confidence intervals, and monitoring systems to measure model quality and operational risk.
- Identify opportunities to safely increase power utilization, reduce stranded capacity, improve cost efficiency, and guide long-term infrastructure investment.
- Lead ambiguous, company-critical technical initiatives across organizations, influencing strategy and aligning stakeholders around scientifically grounded decisions.
- Mentor senior scientists and engineers, raise the technical bar for modeling and forecasting systems, and represent Meta’s work through external publications, talks, or industry engagement.]
- qualifications[
Qualifications
- 10+ years of experience developing statistical, machine learning, simulation, forecasting, optimization, or other quantitative modeling systems
- Experience leading ambiguous, cross-functional technical programs from problem definition through model development, evaluation, deployment, and business impact
- Experience coding in Python, R, C++, Java, or similar languages for data analysis, modeling, simulation, or production systems
- Experience communicating complex technical concepts, assumptions, uncertainty, and tradeoffs to technical and non-technical audiences
- Experience influencing technical strategy across multiple teams or organizations
- PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, Electrical Engineering, Physics, Economics, or a related quantitative field, or equivalent practical experience
- Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Skills
Required:Statistical modelingMachine learningCommunication
Nice to have:OptimizationHigh-dimensional data analysis
Benefits
- Bonus
- Equity
- Benefits
Last updated Oct 23, 2026. Interested? Apply on the company site.
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