Physical Systems Modeling Engineer

The role

You will build simulation and forecasting models for existing and future data centers. You will develop frameworks to capture uncertainty and operational behavior to support planning decisions.

What you will do

• Build models that accurately represent the physical systems inside of a data center
• Develop simulation frameworks that capture uncertainty, growth trajectories, and operational behavior
• Explore how changes in technology, utilization, deployment strategies, and external factors influence future energy consumption
• Analyze historical data to identify patterns, drivers, and sources of uncertainty
• Evaluate model performance and continuously improve assumptions, methodologies, and predictive accuracy
• Collaborate with engineers, researchers, and business stakeholders
• Communicate model assumptions, limitations, and findings clearly
• Take ownership of key modeling components from concept through validation and deployment

Required qualifications

• Bachelor's, Master's, or PhD in a quantitative field
• 1–5+ years of relevant industry or applied research experience
• Experience working with data, mathematical models, simulations, forecasting problems, and time-series analysis
• Experience with forecasting under uncertainty, probabilistic modeling, or scenario generation
• Proficiency in Python or a similar programming language
• Ability to think from first principles and learn unfamiliar technical domains quickly
• Comfort working with ambiguity and open-ended questions
• Strong written and verbal communication skills
• Demonstrated ability to effectively use AI tools in technical workflows

Nice to have

• Exposure to infrastructure systems, energy systems, cloud computing, data centers, telecommunications networks, or other large-scale engineered systems
• Exposure to data center, GPU, CPU power consumption modeling
• Experience modeling data center to grid interaction, such as interconnection, load response, or capacity constraints
• Experience developing models used to support real-world operational or planning decisions
• Experience working with large datasets

Benefits

• Competitive salary
• Equity
• Benefits

About the company

GridCARE is the pioneer of Power Acceleration, using physics-based AI to identify and activate capacity in the electric grid. Founded at Stanford's Doerr School of Sustainability, the company aims to enable hyperscalers and utilities to power AI infrastructure sooner.