Energy Systems Modeling Intern (Python, NumPy)

Job Description: Remote · Part-time (15-20 hrs/week) · San Francisco Bay Area, CA · Unpaid / Academic Credit What You're Walking Into Kelvolta builds physical models of how large electrical loads actually behave, at timescales ordinary metering never sees. Our work spans industrial manufacturing, AI data centers, EV charging, and other markets in which demand is growing fast and the economics of storage turn on behavior nobody has measured. We're a lean team, so interns work close to the physics rather than on the edges of it. "…Learning to build things that actually matter in a startup where I'm constantly learning and adapting."— L. Sanchez, UC Santa Barbara Skills You'll Put to Use and Develop Numerical modeling in Python with NumPy and SciPy: building a defensible simulation of a physical system from published equipment specifications rather than from a ready-made dataset Time-series and frequency-domain analysis: sampling, filtering, and what a measurement at one resolution can and cannot tell you about behavior at another Parameter discipline: every input in our models is sourced and documented, so that any assumption can be checked or replaced by someone who disagrees with it Translating manufacturer datasheets and technical literature into model parameters Who We're Looking For Currently-enrolled (not graduated) upper-division undergraduate or graduate students in Physics, Electrical Engineering, Applied Mathematics, or a related quantitative field. We're looking for people who can code but whose instinct is to ask what the system is physically doing, not just what the data says. Useful background in any combination: Python with NumPy/SciPy, signal processing, power electronics or circuits coursework, MATLAB or Simulink, numerical methods, control systems. If you have ever built a model of something you could not directly measure, say so in your application. Past interns have come in with strong fundamentals and left with experience building production-level work. We care more about what you can do than what year you're in. What You Get Hands-on experience working on real projects with meaningful impact Opportunities to take ownership and contribute to production-level work Direct mentorship from a domain-expert team, including a CEO with 25 years of energy project development experience Exposure to real datasets and practical problem-solving A fast-paced environment that helps you grow quickly A strong portfolio of work you can speak to in interviews Eligibility for academic credit (8–10 units, subject to university approval) Priority consideration for extended or paid opportunities based on performance This is an unpaid internship. All participants are eligible for academic credit, and strong performers are considered for paid roles. Logistics Commitment: 15-20 hours per week