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

About the Company

Equilibrium Energy

San Francisco, CA, USA

101-250

<p>Equilibrium Energy is a well-funded, Series B 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.</p><p>We pride ourselves on our deeply collaborative culture, our honest and direct but respectful communication, the empathy and care that we show for each other, and our balanced, flexible, and remote-first work environment (we have regional hubs in the SF Bay area, Boston and London, but anyone can work from anywhere without paying an influence or access-to-information tax).&nbsp;</p><p>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.</p><p>Equilibrium is composed of deeply knowledgeable industry experts across all our functions, with decades of experience in energy-specific commercial structuring, power systems engineering, machine learning, computational research, operations research, distributed and compute-intensive infrastructure, and modern software &amp; ML engineering. Our experience in the space means we’ve previously built versions of nearly every technical component of our platform. We are now designing them better, and combining them in a holistic and novel way, to achieve global scale and climate impact.&nbsp;</p><p>Come join us!</p>