Gridmatic→
Energy Systems Research Engineer Intern at Gridmatic in Cupertino, CA
InternshipHybridCupertino, CA
Skills
power system operationsunit commitmenteconomic dispatchoptimal power flowpower flow modelingnetwork modelingpython programmingoptimization formulationslinear programmingmixed integer linear programmingeagerness to learn
Job Description
Summary: Gridmatic Inc. is a high-growth startup focused on accelerating the clean energy transition through data and machine learning expertise. The Energy Systems Research Engineer Intern will support electricity market simulation and contribute to the development of SCUC/SCED models, while also working on network security analysis and data processing pipelines.
Responsibilities:
- Develop/maintain network security analysis (NSA) to produce reliability constraints across large-scale ISO systems
- Assist in building and validating SCUC/SCED models, with realistic transmission and contingency constraints
- Help automate NSA for integration into market optimization workflows
- Support data processing pipelines for network, generator, and market datasets across ISOs (ERCOT, PJM, CAISO, etc.)
- Experiment with machine learning approaches to accelerate dispatch or contingency evaluation
- Document results, highlight performance gaps, and propose improvements
Required Qualifications:
- Enrolled in EE, or Energy Systems (MS or PhD student)
- Coursework in power system operations (unit commitment, economic dispatch, OPF)
- Familiarity with power flow and network modeling
- Solid programming skills in Python
- Comfort with optimization formulations (linear, MILP)
- Strong problem-solving skills and eagerness to learn real-world ISO practices
Preferred Qualifications:
- Experience with SCUC/SCED formulations in research or coursework
- Exposure to market data from ISOs (bids, constraints, outage/contingency reports)
- Familiarity with probabilistic or ML-based methods
Required Skills: Power system operations, Unit commitment, Economic dispatch, Optimal power flow, Power flow modeling, Network modeling, Python programming, Optimization formulations, Linear programming, Mixed integer linear programming, Eagerness to learn