Gridmatic

AI Research Scientist

Gridmatic

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $180,000 - $255,000 per year

Job Level

Mid-LevelSenior

Tech Stack

KerasNumpyPandasPythonPyTorchScikit-Learn

About the role

  • 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. The Role We are looking for an AI Research Scientist to expand the horizons of our technology as we work to accelerate the decarbonization of the electricity system. This role involves applied research, and hence the ideal candidate will possess a deep understanding of forecasting techniques, and will develop the knowledge and understanding necessary to apply them to energy markets. They will investigate new technologies to better solve problems we already model, as well as designing solutions to problems we don’t yet solve. In addition, they will work to generalize these solutions so they can be applied more broadly, including on academic datasets for the purpose of sharing with the academic community via publication. A successful candidate will embrace constant learning of both engineering and mathematical concepts, as well as economics and electricity market related topics.

Requirements

  • PhD in ML, statistics, or a related quantitative modeling field A strong publication record: NeurIPS, ICLR, ICML; and/or papers on forecasting and generative/probabilistic models in CV/NLP/Speech venues. Proven experience researching and implementing deep learning models Enthusiasm for learning Understanding of data structures, data modeling and software architecture Deep knowledge of math, probability, statistics and algorithms Fluency in Python and machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn, numpy, and pandas). Excellent skills in communication and teamwork Outstanding analytical and problem-solving skills