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The Company
Gridmatic Inc. is a high-growth startup with offices in the Bay Area and Houston that is accelerating the clean energy transition by applying our expertise in data, machine learning, and energy to power markets. We are the rare startup that has multiple years of profitability without raising venture capital. Gridmatic is a great place to work with a culture that values teamwork, continuous learning, diversity, and inclusion. We move quickly and fix things. We are environmentally and data-driven, with a growth-oriented, academic mindset. We value integrity as much as excellence.
We are looking for interns for our optimization team to help us develop systems to operate grid-scale batteries and flexible loads, and optimize energy trading. For example, we operate a 100 megawatt-hour battery in Texas and a 400 megawatt-hour battery in California. The ideal intern candidate will have a strong programming background, be familiar with convex optimization, and have machine learning experience. During the internship, you will use our optimization and backtesting framework to do analysis and develop new strategies. You will also have opportunities to extend the framework with new functionality or new asset types.
What you might work on:
- Develop understanding of the rules for trading, battery, and flexible load participation in energy markets.
- Use our backtesting framework for simulating performance on historical data.
- Characterize risk-return trade-offs of different optimization-based approaches to asset operation.
- Adapt existing optimization formulations to new asset types.
- Develop predictive models that generate optimization inputs, such as predicting future energy prices
- Present results to the optimization team, Gridmatic as a whole, and Gridmatic clients.
- Write and review code, with attention to performance and readability.
You might be a good fit if you:
- Write robust code in Python.
- Have experience applying mathematical optimization to real world applications.
- Are familiar with optimization libraries such as CVXPY.
- Are experienced with classical or deep learning based time series forecasting
- Have excellent communication and teamwork skills.
- Have enthusiasm for learning.
- Knowledge of the energy industry is a plus.
We recognize some candidates may hesitate to apply if they do not have all the listed skills. We encourage interested individuals to apply if they have relevant skills even if they do not have experience in every listed area.
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We recognize some candidates may hesitate to apply if they do not have all the listed skills. We encourage interested individuals to apply if they have relevant skills even if they do not have experience in every listed area.
Join our team and make a difference! Click below or email us at [email protected].
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