Energy Optimization Specialist

5 days ago


Cupertino, California, United States Gridmatic Full time

Gridmatic is a pioneering startup in the clean energy sector, accelerating the transition to a sustainable future by harnessing data, machine learning, and energy expertise. With a proven track record of profitability without venture capital, we offer a unique work environment that values teamwork, continuous learning, diversity, and inclusion. Our culture is characterized by a growth-oriented mindset, emphasizing integrity as much as excellence.

We are seeking an Energy Optimization Specialist to expand our technology horizons and drive the decarbonization of the electricity system. This role involves applied research, requiring a deep understanding of mathematical optimization methods. The ideal candidate will develop the necessary knowledge and skills to apply these methods to energy markets, investigating new approaches to optimization problems and designing formulations for unsolved issues. A successful candidate will demonstrate a commitment to constant learning, embracing engineering, mathematical, economic, and electricity market-related topics.

The scope of this position includes:
• Developing a thorough understanding of mathematics and mechanisms underlying energy markets to identify and adapt effective solutions.
• Staying abreast of the latest advances in optimization research to determine if novel methods hold promise for addressing challenges in the electricity market space.
• Designing and analyzing optimization formulations for battery operations, energy trading, and other business areas.
• Promoting optimization-driven decision making and mathematical modeling across the organization.
• Authoring research papers in optimization, operations research, and decision making under uncertainty.
• Writing and reviewing code, prioritizing performance and readability.

Candidates with the following qualifications may be well-suited for this role:
• Strong publication record demonstrating expertise in mathematical optimization.
• Earned a PhD in applied mathematics, operations research, or a related quantitative field.
• Deep knowledge of optimization techniques, particularly for convex optimization problems.
• Proven experience researching and applying optimization techniques.
• Proficiency in writing robust code in Python.
• Familiarity with optimization libraries like CVXPY.
• Outstanding analytical and problem-solving skills.
• Excellent mentorship, communication, and teamwork skills.
• Enthusiasm for continuous learning. Knowledge of the energy industry is highly beneficial.

We encourage interested individuals to apply, even if they do not meet every listed requirement. An attractive salary range is $205,000 - $250,000 per year.



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