Jobs

Internship, Commercial Charging Product Management, Energy Engineering (Summer 2026)
Palo Alto, California
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On-site
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Internship
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Today
Consider before submitting an application:
This position is expected to start May 2026 and continue through summer term (ending approximately August 2026 or later, if available). We ask for a minimum of 12 weeks, full-time (40 hours/week) and on-site, for most internships. Our internship program is for students who are actively enrolled in an academic program. Recent graduates seeking employment after graduation and not returning to school should apply for full-time positions, not internships.
International Students: If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. You must be able to work 40 hours per week on-site. Many students will be limited to part-time during the academic year.
The Internship Recruiting Team is driven by the passion to recognize and develop emerging talent. Our year-round program places the best students in positions where they will grow technically, professionally, and personally through their experience working closely with their manager, mentor, and team. We are dedicated to providing an experience that allows the intern to experience life at Tesla by including them in projects that are critical to their team’s success.
As a Hardware Product Management Intern, you will help define and commercialize Tesla’s industrial energy hardware product offerings for Utility and Large Industrial clients.You will leverage your expertise to develop market and product requirements needed to deliver industry-leading industrial energy hardware products. You will also be a key member of a cross-functional Product Management team that supports the ongoing development of technical content for sales, service, and engineering teams for Tesla’s industrial energy products.
Charging Product Management Internship
Bring impactful EV and Robot Charging solutions to the market. The Tesla Commercial Charging Product team is responsible for scoping and delivering the Software and Hardware roadmap for Supercharging, Commercial AC Charging and next gen charging products for the Robotaxi and Optimus Robot. In this role, you will take ownership of select Commercial Charging roadmap deliverables and be responsible for discovering customer pain points, writing the Product Requirements Document and working with cross-functional teams to launch the solution. You will work closely with engineering, design and business teams to make tradeoffs and report on outcomes to leadership.
Location: Palo Alto, CA
What You'll Do
Compensation and Benefits
As a full-time Tesla Intern, you will be eligible for:
$20.00 - $50.00/hour + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
, Tesla
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About Tesla

Tesla
PublicA financial leasing taxi company that provides vehicles to customers
140,000+
Employees
Ciudad De Panamá
Headquarters
$800B
Valuation
Reviews
3.1
5 reviews
Work-life balance
1.5
Compensation
1.2
Culture
1.3
Career
1.8
Management
1.1
15%
Recommend to a friend
Pros
Strong financial performance
Revenue growth
Company achieving targets
Cons
Poor compensation and raises below inflation
Union-busting and anti-labor practices
Unpaid work demands and wage theft
Salary Ranges
1,397 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · ASSOCIATE MANAGER, LOGISTICS
2 reports
$131,600
total per year
Base
$114,400
Stock
-
Bonus
-
$131,600
$131,600
Interview experience
4 interviews
Difficulty
3.5
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 75%
Negative 25%
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Take-home Assignment
5
Panel Interview
6
Offer
Common questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Machine Learning Concepts
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