About the Company
Founded in December 2019 and incorporated in August 2020, ElectricFish Energy, Inc. (“ElectricFish”) is dedicated to bringing energy resilience to transportation. Our turnkey energy storage solutions provide flexible energy resources at sites to help electrify transportation and decarbonize without compromising the grid’s stability. At scale, our network of energy storage will serve as a decentralized ‘utility of the future’ prepared to meet the energy needs of EVs and a renewable powered grid.
Our product provides equitable access to public, ultrafast electric vehicle charging, thus enabling accessible transportation electrification while also providing electricity reliability-as-a-service with the network capacity to offset additional fossil fuel electricity generation in high demand hours. At scale, our network of distributed energy storage stores clean, low-cost electricity that mitigates marginal emissions associated with fossil fuel generation dispatched to match loads.
Why we need you
To continue to build out our vision and grow, we need someone like you to lead the development and testing of algorithms for the operation of our system optimization and grid management intelligence products. We’re looking for a passionate, exceptional, and highly motivated candidate with strong engineering, research, and leadership experience to take on one of the most important roles within our organization. You’ll be helping us bring smart, distributed ultrafast EV charging-integrated energy storage to the mainstream, eliminating EV range anxiety, and accelerating vehicle fleet electrification.
About the Role
In your role, you will own the product roadmap and strategy, as well as the definition of requirements. Functions such as managing iterations, feature development and feature improvement integral to your role. Your core functions also include:
Lead the designing, developing, and deploying of the team’s core algorithms for Energy Storage application for serving EV DC fast charging, behind-the-meter and front-of-the-meter energy services.
Write optimization models using GAMS, OPL and CPLEX to compute dispatch schedules of energy storage system.
Understand business case to design new features of the existing optimization model.
Test new features using unit tests and simulation framework in Python.
Run existing test vectors to perform regression testing.
Perform literature review to propose new state of the art optimization algorithms relevant to developing ESS optimization engine.
Graduate or Advanced Degree (e.g., MS, Ph.D.) in Operations Research, Applied Mathematics, Computer Science, Physics, Engineering, or related field.
Experience formulating, designing, and deploying optimization models with development tools such as OPL, AMPL, GAMS, etc.
Fluency in at least one programming or scripting language (Python, Java, C, C++, etc.).
Working knowledge of statistics.
Strong ML research and engineering utilizing established and emerging architectures in energy applications.
Experience working with large datasets and time-series data.
Familiarity with Software Change, Configuration Management and Build Processes in a complex environment.
Ability to approach problem solving strategically, demonstrating first principles understanding.
A deep attention to detail with an innate sense of accountability, and an execution-oriented mindset.
Experience and proven effectiveness working in high-impact, diverse and cross-disciplinary teams.
Experience with deep reinforcement learning models.
Experience with stochastic modeling, particularly in energy and electric utility problem applications.
Experience with probabilistic graphical models.
A portfolio of relevant projects (e.g., GitHub) or peer-reviewed publication.
Previous experience working in a startup environment.
Experience leading an engineering team in the cleantech (energy systems and/or EV charging) space.
Worked on a software product that interacts with hardware.