Energy Systems Research Engineer

Gridmatic is a high-growth startup and a new kind of energy company, delivering affordable, clean power by optimizing renewable energy and grid-scale batteries. With offices in the Bay Area and Houston, we bring together Silicon Valley-style innovation with deep, hands-on expertise in real-world power markets and energy retail.

As solar and wind become the fastest-growing sources of electricity, variability from weather and grid conditions makes energy prices more volatile. Gridmatic tackles this challenge with industry-leading forecasting and optimization-and gives our team the opportunity to work on problems that truly matter. Forecasting and trading energy are the foundation of what we do. We ingest large-scale data-weather, prices, load, and grid conditions-to build probabilistic machine learning forecasts that drive real operational decisions. Our work directly determines when power is bought, stored, or deployed, turning uncertainty into value for customers and the grid.

Our impact is measurable. Gridmatic is the most profitable participant in ERCOT's wholesale market and operates the top-performing battery asset in CAISO. Profitable without venture capital, we offer a collaborative, low-ego environment where rigorous thinking, autonomy, and continuous learning are core to how we work.

Responsibilities

• Develop and implement advanced optimization models for Security-Constrained Unit Commitment (SCUC), Security-Constrained Economic Dispatch (SCED), and other electricity market clearing processes.
• Model electricity market behavior from the participant perspective (generation, storage, demand response), including bidding strategies, forecasting, and risk exposure.
• Simulate market outcomes under various conditions, including congestion, renewable variability, storage operations, and policy changes.
• Develop tools for network modeling, power flow analysis, and contingency analysis.
• Work closely with engineers to productionize models, ensuring scalability and reliability.

Qualifications

• MS or PhD in Electrical Engineering, Power Systems, Operations Research, or a related field.
• Strong background in optimization (mixed integer, stochastic, robust, convex) with applications to SCUC/SCED or other electricity market problems.
• Familiarity with AI techniques in energy markets.
• Solid understanding of ISO/RTO market rules and participant behavior.
• Proficiency in Python and experience handling large datasets.

Bonus Skills

• Experience with production cost modeling tools, HPC/cloud computing, or power system simulators.

Join our team and make a difference! Click below or email us at [email protected].

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.