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Gridmatic

AI-driven optimization of renewable assets

Energy Systems Research Engineer Intern

Power Systems EngineeringPosted on Nov 13
InternshipCupertino, CA, USANo salary listedIn-person

About the Job

Requirements

  • Be enrolled as an MS or PhD student in Electrical Engineering or Energy Systems.
  • Have coursework in power system operations, including unit commitment, economic dispatch, and optimal power flow.
  • Be familiar with power flow and network modeling.
  • Have solid programming skills in Python.
  • Be comfortable with optimization formulations, including linear and mixed-integer linear programming.

Responsibilities

  • Develop and maintain network security analysis to produce reliability constraints across large-scale independent system operator systems.
  • Assist in building and validating security-constrained unit commitment and security-constrained economic dispatch models with realistic transmission and contingency constraints.
  • Help automate network security analysis for integration into market optimization workflows.
  • Support data processing pipelines for network, generator, and market datasets across independent system operators, including ERCOT, PJM, and CAISO.
  • Experiment with machine learning approaches to accelerate dispatch or contingency evaluation.
  • Document results, highlight performance gaps, and propose improvements.

Desired Qualifications

  • Have experience with security-constrained unit commitment or security-constrained economic dispatch formulations in research or coursework.
  • Have exposure to independent system operator market data, including bids, constraints, and outage or contingency reports.
  • Be familiar with probabilistic or machine-learning-based methods.

About the Company

Gridmatic

AI-driven optimization of renewable assets

Gridmatic uses artificial intelligence to improve the profitability and reliability of renewable energy assets. It serves three client groups: generators of renewables, operators of energy storage, and consumers of renewable energy. The product suite analyzes market data with machine learning to forecast energy prices, manage price and performance risk, and optimize revenue from energy transactions—especially for storage assets that must balance risk and availability. Unlike others that focus on a single segment, Gridmatic combines AI analytics with energy market expertise to optimize both generation and procurement across markets. Its goal is to accelerate clean energy adoption by making renewable energy cheaper, more predictable, and easier to deploy at scale, supporting decarbonization and a more reliable grid.

Company size
51-200
Company stage
Early VC
Total funding
$6M
Headquarters
Cupertino, CA
Founded
2020

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