Machine Learning Scientist (Staff / Sr Staff) - Power Markets

Equilibrium Energy is a well-funded, Series A clean energy startup backed by some of the most prominent institutional investors in climate. We are building a digital native power company operating at the intersection of grid variability, market volatility, economic optimization, commercial structuring, and risk management, across the end-to-end power value chain. Our mission is to accelerate our collective path to climate, energy, and societal equilibriums. Our goal is to become one of the next-generation, digital-native, end-to-end global clean power companies that reshapes the energy industry. New colleagues will share our vision that a next-generation energy company must be built from the ground up on deep industry expertise combined with an unwavering commitment to modern digital approaches. We design our commercial strategies, operational approaches, and product suites so as to best leverage data-driven insights, automated workflows, ML-infused pipelines, and fully automated decision engines. These capabilities are enabled by our progressively modern software stack and engineering best practices, which in turn provide the scalable platform we need to put a serious dent in carbon emissions. We’re looking for collaborative, talented, passionate and resourceful folks to join our team and help us lay the foundation for our important mission and ambitious plan.

• Competitive base salary and a comprehensive medical, dental, vision, and 401k package
• Opportunity to own a significant piece of the company via a meaningful equity grant
• Unlimited vacation and flexible work schedule
• Ability to work remotely from anywhere in the United States & Europe, or join one of our regional hubs in Boston, SF Bay Area, or London
• Accelerated professional growth and development opportunities through direct collaboration and mentorship from leading industry expert colleagues across energy and tech

• Passion for clean energy and fighting climate change
• An advanced degree in computer science, data science, machine learning, artificial intelligence, operations research, engineering, or related quantitative discipline
• 4+ years experience in data science, research science, machine learning, or similar role, applying and adapting deep learning, graph neural networks, or reinforcement learning techniques to time series regression & forecasting problems
• 2+ years experience in the electricity & energy domain (e.g. electricity price forecasting, congestion prediction etc)
• 3+ years experience with python and the supporting computational science tool suite (e.g. numpy, scipy, pandas, scikit-learn, tensorflow, etc.)
• Experience developing, releasing, and tracking performance of ML models in production
• Experience communicating mathematical concepts, analytical results, and data-driven insights to both technical and non-technical audiences
• A collaboration-first mentality, with a willingness to teach as well as learn from others