Energy Systems Modeling Intern (Python, NumPy)
Kelvolta
United States25–27 yrs1h agovia LinkedIn
This job at a glance
- Who can apply
- 25–27 years of experience
- Must know
- Lean / Six SigmaPythonNumPyCircuit designMATLABNetworking
- Work
- On-site in United States · internship
- Pay
- Not stated by the employer.
- Skill demand
- Python28%Circuit design9%Lean / Six Sigma4%NumPy2%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 3, 2026 · still open
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About Kelvolta
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.
Key Responsibilities
- 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 understanding what a measurement at one resolution can and cannot tell you about behavior at another
- Parameter discipline: ensuring every input in our models is sourced and documented, so that any assumption can be checked or replaced
- Translating manufacturer datasheets and technical literature into model parameters
Requirements & Tech Stack
- Python with NumPy/SciPy
- Signal processing
- Power electronics or circuits coursework
- MATLAB or Simulink
- Numerical methods
- Control systems
Qualifications
- Currently-enrolled (not graduated) upper-division undergraduate or graduate students in Physics, Electrical Engineering, Applied Mathematics, or a related quantitative field.
- Ability to code with an instinct to ask what the system is physically doing, not just what the data says.
- Experience building a model of something you could not directly measure is a plus.
Internship Details
- Commitment: 15-20 hours per week
- Duration: Minimum 10 weeks
- Format: Remote, Part-time, Unpaid / Academic Credit
- Location: San Francisco Bay Area, CA
- Start Date: Flexible; prefer November start date
- Academic Credit: Eligibility for academic credit (8–10 units, subject to university approval)
- Potential: Priority consideration for extended or paid opportunities based on performance.
Interviews will be approximately 15 minutes and are requested for the week of November 9.