First Engineer (Data & Control Algorithms)

Energy storage systems can generate revenue from numerous sources. As our first dedicated engineer, you will be responsible for expanding our core intelligence. Your primary role will be to design, build, and deploy the data infrastructure and advanced control algorithms necessary to identify, pursue, and continuously improve these revenue streams.  In a fast-moving startup environment, unexpected challenges and opportunities frequently arise. We’re looking for someone who thrives in ambiguity, enjoys wearing multiple hats, and is eager to contribute wherever needed — whether that’s tackling technical hurdles, supporting operations, or lending a hand across teams.

You will:

• Design and implement robust, end-to-end data pipelines (ETL, feature engineering, storage solutions, visualization) to collect, process, and analyze data from energy usage, market signals, and system performance.
• Research, develop, and simulate advanced control algorithms (e.g., Model Predictive Control, Reinforcement Learning, dynamic programming, heuristic optimization) for optimal energy dispatch decisions that maximize revenue across diverse grid services and market conditions.
• Validate algorithm performance through rigorous numerical simulations (primarily using Python) and hardware-in-the-loop testing environments.
• Deploy, monitor, and continuously iterate on your algorithms, defining key performance indicators and driving improvements based on real-world data.
• Clearly communicate technical concepts, findings, and recommendations through reports and presentations to both technical colleagues and non-technical stakeholders, including the founding team.
• Influence the technical direction of our data and algorithmic platform as the foundational engineering hire.
• Contribute across the organization. As part of an early-stage startup, you’ll have the opportunity to take on a wide variety of responsibilities beyond your core role. This may include supporting sales efforts, assisting with system installations, or helping resolve technical support issues. We value flexibility, initiative, and a collaborative spirit as we build and scale together.

Requirements

• Bachelor's, Master's, or PhD in Electrical Engineering, Computer Science, Data Science, Applied Math, or a related highly quantitative or engineering field (Master's or PhD is strongly preferred).
• Experience in building data analysis pipelines and applying statistical modeling techniques (Strong proficiency in Python with libraries like pandas, Polars, scikit-learn, etc., and experience with SQL).
• Hands-on background in the development, simulation, and ideally deployment, of control algorithms (Experience with MATLAB/Simulink or advanced Python control toolboxes).
• Experience or strong theoretical understanding of Machine Learning concepts, particularly their application in control or optimization problems (e.g., Reinforcement Learning).
• Excellent programming skills and strong command of version control (Git).
• Exceptional problem-solving skills and the ability to structure and tackle complex, ambiguous technical challenges.
• Ability to work independently and proactively, taking ownership of technical areas from initial research to production.

Further desirable qualifications include:

• Prior experience in energy systems, grid markets, IoT, or industrial controls.
• Experience with cloud computing platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Background in optimization theory or energy economics.