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The salary range is $180,000 - $240,000 a year.
This information is not specified in the job description.
A Master’s degree in Electrical Engineering or Power Systems Engineering with 4+ years of experience or a Ph.D. is required, along with experience in Python collaborative development, power systems network modeling (power flow, contingency analysis, etc.), and proficiency with tools like PSS/E or PSLF. Knowledge of optimization techniques and familiarity with SCUC/SCED are also essential.
Gridmatic values teamwork, continuous learning, diversity, and inclusion, with a growth-oriented, academic mindset that is environmentally and data-driven. They emphasize integrity as much as excellence and move quickly to fix things.
Strong candidates will have a Master’s or Ph.D. in Electrical Engineering or Power Systems, 4+ years of industry experience, hands-on expertise with power system simulation tools and network modeling, plus bonus skills like production cost modeling with PLEXOS or UPLAN and IEEE involvement.
AI-driven optimization for renewable energy assets
Gridmatic uses artificial intelligence to improve the performance and profitability of renewable energy assets. It serves renewable energy generators by predicting energy prices and managing risks, while helping storage operators optimize revenue and minimize non-performance risks. For consumers, Gridmatic aims to lower energy costs and support renewable energy procurement. The company stands out by combining advanced algorithms with market expertise to modernize energy markets and contribute to decarbonization.