About the role#
As a thermal system modeling intern, you will support the Energy Engineering team. You will work on vapor compression cycle modeling to help optimize the performance of Tesla energy products, including Megapack, Supercharger, and Powerwall. This role requires applying engineering fundamentals to thermal systems.
What you'll do#
- Assist with the development of vapor compression cycle models.
- Identify the cooling capability and efficiency potential of refrigerant systems across various applications.
- Build a modular compression cycle platform to support fast iteration in mechanical design.
What you'll need#
- Current pursuit of a degree in Mechanical Engineering, Chemical Engineering, or a related field.
- A solid understanding of thermodynamics, heat transfer, and the vapor compression cycle.
- Familiarity with modeling compressors, refrigerants, and heat exchangers.
- Experience working with Python or Matlab.
Location & details#
- Location: Palo Alto, California.
- Terms: Winter 2027 or Summer 2027.
- Commitment: Full-time (40 hours per week) and on-site for a minimum of 12 weeks.
- This is a paid internship.
About Tesla
Tesla produces electric vehicles, battery storage systems, and solar energy products. Founded in 2003, the company operates six vertically integrated factories across three continents. It is headquartered in Austin, Texas, and employs over 10,000 people. The organization designs, manufactures, sells, and services its products internally.
How to get in at Tesla
Applying early at Tesla provides a distinct advantage because recruiters review candidates before the applicant pool becomes unmanageable. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you apply among the first and get seen before the pile grows. Reaching out to the right people often yields better results than submitting to a general queue. Intern Insider surfaces the recruiters behind the company roles so you can contact them directly to ask about the position or a referral, which materially improves your response rates.
