What to Expect

Consider before submitting an application:  

This position is expected to start around January or February 2025 and continue through the entire Spring term (i.e. through May 2025) or into Spring/Summer 2025 if available. We ask for a minimum of 12 weeks, full-time and on-site, for most 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.  

Internship Program at Tesla  

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. 

What You’ll Do

Our team develops and performs cutting edge and industry leading qualification techniques of battery cells that influence the future direction of Tesla products. We are looking for an Engineering Intern who can independently lead technical projects, analyze and summarize large amounts of data, and use critical engineering judgement to plan, execute, and report. 

Leverage the vast amounts of data generated throughout the cell qualification process to help Tesla design and produce safer, lower-cost, and high-performance cells. 

Analyze and visualize data to identify trends and risks in cell programs  

Create tools for rapid analysis of datasets and characterization techniques 

Aid in designing tests and analyzing data to understand fundamental battery degradation modes 

What You’ll Bring

Currently pursuing a degree in Data Science, Reliability Engineering, Math, Mechanical Engineering, Materials Science or a related field 

Understanding of Design for Reliability and Design of Experiments 

Proficient in Python data analysis and visualization 

Proficiency in statistical modeling and scripting, knowledge of Design of Experiments, DFMEA and Design for Reliability, experience collaborating with design, manufacturing, and testing teams, proficiency in data analysis 

Familiarity with reliability software tools and Weibull analysis, knowledge of mechanical and electrochemical battery cell failure modes, Data Science, Data Engineering 

Knowledge on lithium-ion cell life modeling and electrochemical mechanism is a plus but not required

Palo Alto, California

Intern/Apprentice