As a technical owner within Server Demand Planning, you drive server demand forecasting and demand-supply matching for your area and close on feasible supply requirements: you forecast near- and long-term server capacity demand by rack/hardware type and region, and you build the operations research models that match that demand to supply so we land the right long-term DC & hardware infra requirements, in the right place, at the right time.
Responsibilities
Own and drive a multi-horizon server/MW demand forecast (near term through 2-5+ years), producing trusted, reproducible release to inform decisions
Aggregate and normalize demand signals from short-term demand and product groups into a single trusted statistical long-term demand plan
Formulate and solve the demand-supply matching problem using operations-research models that reconcile forecasted demand with hardware roadmaps, cooling, lead times, and power constraints to inform the Plan of Record
Build across the full modeling spectrum: production-grade optimization and forecasting systems and prototype models and heuristics that answer a leadership question or unblock a decision
Partner with IDC engineering, site selection, and hardware strategy teams to align next-generation data center designs, rack sizing, and hardware roadmaps with demand, eliminating stranded power, cooling, and space capacity
Requirements
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
MS in a quantitative field (Operations Research, Industrial Engineering, Applied Math, Statistics, CS, or related)
PhD in Operations Research, Industrial Engineering, Management Science, or a related quantitative field
Nice to have: time series forecasting
Nice to have: hierarchical/probabilistic forecasting
Research Engineer to join the ACT Character team, working at the intersection of research and engineering to bring cutting-edge AI and algorithmic capabilities into our character pipeline.
Responsibilities
Contribute to the ACT Character R&D team's work advancing the quality of real-time characters in Unreal Engine
Collaborate with researchers, artists, and engineers across the full character creation process (from scanning and performance capture to animation and rendering)
Identify points of friction in existing processes and develop techniques to automate and improve the art team's efficiency
Research and develop prototypes that solve hard problems in the space of digital characters
Stay current on the latest research in digital characters and adjacent fields to inform the team's direction
Requirements
MSc/Ph.D. in computer science, electrical engineering, or a related field
Provide analytical decision‑support for Universal Destinations & Experiences leadership, influencing data‑driven operational and workforce decisions using industrial engineering, operations research, and advanced analytics.
Responsibilities
Design, operationalize, and sustain end‑to‑end analytical and decision-support solutions using industrial engineering and business analytics principles.
Apply structured analytical techniques—including probability and statistics, process flow analysis, queuing theory, mathematical optimization, scenario modeling, and prescriptive optimization solvers to diagnose problems.
Develop and maintain decision-support models for labor planning, workforce utilization, budgeting, scheduling, and hiring strategies.
Partner closely with operational leaders to define problems, frame decisions, and drive adoption of data-driven solutions.
Acquire and prepare data using database querying tools and modern data pipelines.
Requirements
Bachelor’s degree in Industrial Engineering
Operations Research
Management Science
Decision Science
Nice to have: Master’s degree in Industrial Engineering, Operations Research, Management Science, or Decision Science
The role involves building and extending large-scale simulations of global traffic placement, solving capacity planning as constrained optimization, building production forecasting for peak demand, and leading technical direction across multiple teams.
Responsibilities
Build and extend large-scale simulation of global traffic placement: how traffic shifts across edge sites as demand grows and as sites, peering links and backbone paths fail.
Work with the load-balancing team on simulation fidelity and performance, and validate results against production behavior and live failure tests
Formulate and solve capacity planning as constrained optimization: where to add compute, peering and caches, given space, power, supply, latency and failure constraints.
Build and tune the solvers
Plan capacity for the browsers, proxies and caches Meta's services and AI agents use to reach the internet, and find which one becomes the bottleneck as Meta's internet access needs grow.
Design systems of systems: decompose complex problems into well-bounded services with clear interfaces, and reason about how they interact, fail, and scale together
Research Scientist, Demand ForecastingMeta · Menlo Park, US
Lead Data Scientist – Demand Forecasting & OptimizationSymphonyAI · Bengaluru, India
Data ScientistManagem · Casablanca, Morocco
Backend Software Engineer - Mission Planning StrategyLoft Orbital Solutions · Toulouse, France+2 more
Engineer, IndustrialUniversal Orlando · Orlando, US