Energy Engineering - Software Engineer/Data Scientist (Summer 2023)

Disclaimer: This position is expected to start around May 2023 and continue through the entire Summer term (i.e. through September) or into early Fall 2023 if available. We ask for a minimum of 12 weeks, full-time, for most internships. Please consider before submitting an application.

International Students: If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. Again, please do not apply until you know you can work 40 hours per week. 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.

About the team

The Energy and Supercharging reliability engineering team is in charge of helping Tesla optimize product design and validate the most compelling and reliable for our customers. For this purpose, the team is responsible for both designing/building automated test equipment to validate current and future products and collecting data to enable the reliability physics analyses.

The Intern will utilize large-scale data and help Tesla engineers design and validate the most compelling and reliable products for our customers. The reliability data team collects real-time life data from test and fleet (energy, charging, and vehicle products) and is responsible for retrieving, analyzing and summarizing results to cross-functional teams. The team provides support through the whole design cycle by building software and statistical tools that orchestrate all the reliability physics analyses.

• Answer complex questions on fleet usage and behavior to enable proactive monitoring, grow reliability, and minimize field failures


• Build scalable data pipelines to deploy fleet health monitoring models


• Apply modern statistical frameworks to support Design for Reliability and associated corrective actions


• Work closely with cross-functional teams to create/interpret/validate numeric models of fielded and in-test products


• Build visualizations to effectively communicate results

Excellent SW skills (proficiency in Python - Data Science stack)

• Strong MLOps and DevOps skills


• Solid understanding of statistics (Statistical Learning, Bayesian Models,)


• Strong knowledge of data structures and architectures and languages such as SQL


• Strong verbal and written communication skills


• Experience with scalable Machine Learning & time-series modeling


• PySpark and Big Data frameworks


• Familiarity with CI/CD


• Ability to code robust-apps (potentially interfacing with data streams, etc.)

Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.

Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.

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