Internship, Software Machine Learning Engineer, Reliability Energy Engineering (Summer 2025)

Consider before submitting an application:

This position is expected to start May 2025 and continue through the entire Summer term (i.e. through August/September 2025) or into Fall 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.
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 Role
The Intern will utilize large-scale data and models to help Tesla engineers design and validate the most compelling and reliable products for our customers.
You will collect some of the largest datasets of real-time test, factory and fleet of Vehicle & Energy products and develop statistical models to unlock decision making on prognostics and targeted design actions. Your work will impact and be utilized by millions of Tesla's customers.

Responsibilities

• Design, develop, train, and deploy predictive / control models of physical degradation, usage and system performance
• Build robust, flexible and automated software tools to enable complex analysis of real-time fleetDesign scalable and reliable data pipelines to productionize and monitor both new and existing models
• Answer complex questions on fleet usage and behavior to enable proactive monitoring, grow reliability, and minimize field failures
• Build visualizations to effectively communicate results

Requirements

• Pursuing a degree in Computer Science or Engineering in a related field
• Excellent SW skills and proficiency in writing production-quality code in Python
• Excellent understanding of linear algebra, probabilistic theory, numerical optimization, and deep learning, with hands-on implementation experience
• Practical experience with a low-level (C, Rust) and database (SQL) programming languages
• Familiarity with PySpark and Big Data frameworks

• Familiarity with CI/CD
• Ability to code robust apps (potentially interfacing with data streams)

• General knowledge of physics and engineering principles

Compensation and Benefits
Benefits

As a full-time Tesla Intern, you will be eligible for:

• Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deduction
• Family-building, fertility, adoption and surrogacy benefits
• Dental (including orthodontic coverage) and vision plans. Both have an option with a $0 payroll contribution
• Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Medical Plan with HSA
• Healthcare and Dependent Care Flexible Spending Accounts (FSA)
• 401(k), Employee Stock Purchase Plans, and other financial benefits
• Company Paid Basic Life, AD&D, and short-term disability insurance
• Employee Assistance Program
• Sick time after 90 days of employment and Paid Holidays
• Back-up childcare and parenting support resources
• Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
• Commuter benefits
• Employee discounts and perks program
Expected Compensation

$20.00 - $50.00 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.

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