Research Scientist, Infrastructure Modeling and Reliability

Meta; United States; Presencial; USD 271.000 - 347.000; Jornada completa

Descripción de la vacante

Meta is seeking an experienced Research Scientist or Applied Scientist to define and build new modeling approaches for power utilization across our infrastructure.

This role leads the development of statistical and machine learning models that monitor power consumption, project peak demand, quantify uncertainty, and inform how Meta maximizes usable power within failure domains while maintaining target reliability levels.

Formación

• 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 communicating complex technical concepts, assumptions, uncertainty, and tradeoffs to technical and non-technical audiences.

Responsabilidades

• 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.
• 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 other scientists and engineers, raise the technical bar for modeling and forecasting systems, and represent Meta's work through external publications or talks.

Conocimientos

Python

R

C++

Java

Statistical modeling

Time-series forecasting

Bayesian modeling

Descripción del empleo

Meta builds technologies that help people connect, find communities, and grow businesses. Meta's infrastructure supports services used by billions of people, and operating that infrastructure efficiently requires increasingly sophisticated modeling of demand, utilization, reliability, and physical resource constraints.We are seeking an experienced Research Scientist or Applied Scientist to define and build new modeling approaches for power utilization across Meta's infrastructure. This role will lead the development of statistical and machine learning models that monitor power consumption, project peak demand, quantify uncertainty, and inform how Meta maximizes usable power within failure domains while maintaining target reliability levels. Qualified candidates will have has deep experience modeling high-dimensional, noisy, and interdependent systems, and has demonstrated the ability to translate scientific advances into production systems that influence large-scale infrastructure strategy.Research Scientist, Infrastructure Modeling and Reliability Responsibilities:Define the scientific and technical strategy for modeling power consumption, peak risk, and reliability tradeoffs across large-scale infrastructure systemsDevelop statistical, machine learning, and/or optimization models that forecast power demand, estimate peak distributions, quantify uncertainty, and support operational decision-makingBuild approaches that reason about high-dimensional signals, correlated demand, failure-domain constraints, reserve margins, and reliability targetsPartner with engineering, capacity planning, data center, energy, hardware, operations, and finance teams to translate model outputs into infrastructure planning and utilization decisionsEstablish evaluation frameworks, backtesting methods, confidence intervals, and monitoring systems to measure model quality and operational riskIdentify opportunities to safely increase power utilization, reduce stranded capacity, improve cost efficiency, and guide long-term infrastructure investmentLead ambiguous, company-critical technical initiatives across organizations, influencing strategy and aligning stakeholders around scientifically grounded decisionsMentor other scientists and engineers, raise the technical bar for modeling and forecasting systems, and represent Meta's work through appropriate external publications, talks, or industry engagementMinimum Qualifications:10+ years of experience developing statistical, machine learning, simulation, forecasting, optimization, or other quantitative modeling systemsExperience leading ambiguous, cross-functional technical programs from problem definition through model development, evaluation, deployment, and business impactExperience coding in Python, R, C++, Java, or similar languages for data analysis, modeling, simulation, or production systemsExperience communicating complex technical concepts, assumptions, uncertainty, and tradeoffs to technical and non-technical audiencesExperience influencing technical strategy across multiple teams or organizationsPreferred Qualifications:Experience with infrastructure, capacity planning, power systems, energy systems, data centers, reliability engineering, distributed systems, supply-chain optimization, or resource allocationExperience developing peak-demand forecasts, confidence intervals, risk estimates, anomaly detection, or backtesting frameworksExperience mentoring senior technical contributors and building scientific communities across organizationsDemonstrated record of industry-level technical leadership, such as defining new research directions, influencing company strategy, publishing in leading venues, or shaping external technical standardsExperience building models that support operational decisions under explicit reliability, safety, cost, or utilization constraintsExperience applying optimization, operations research, or decision science to large-scale resource planningExperience modeling high-dimensional, sparse, noisy, or strongly correlated data in production environmentsExperience with time-series forecasting, probabilistic forecasting, Bayesian modeling, extreme-value modeling, causal inference, stochastic processes, simulation, or uncertainty quantificationAbout Meta:Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [e-mail].$271,000/year to $347,000/year + bonus + equity + benefitsIndividual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.