What to Expect

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. 

This is a cross functional internship working with Tesla Audio and Sensor teams. In this role you will be helping to develop next generation features of Tesla cars utilizing existing sensors and hardware.

You are motivated, self-starting and thrive in a fast-paced development environment. You have ability to absorb technical documentation and learn quickly. You are comfortable developing both hardware and software. You have strong debug skills and have experience working on large codebases. You are familiar with testing and validating complex software systems.

What You'll Do

• Organize capturing car camera data and help develop machine learning (ML) models that accurately track objects
• Debug and maintain software for data capture, storage, and large-scale ML model training
• Validate models using ground truth from mechanical test jigs and real-world datasets

What You'll Bring

• Currently pursuing a Degree in Electrical Engineering, Software Engineering, Computer Science / Engineering, or a related field
• Deep Learning Fundamentals: understanding of neural networks, especially CNNs, and their application to spatial data
• PyTorch: ability to read, modify, and train models using PyTorch, including custom architectures and data pipelines
• Model Training & Evaluation: experience with training, validation, and metrics (MAE, Huber loss), preferably using PyTorch Lightning
• Computer Vision experience, ideally with 3D data
• Point Cloud Processing: experience converting 3D point clouds to raster grids for CNN input
• Experience with camera hardware, calibration techniques
• Strong Python coding skills (numpy, pandas, scientific libraries); strong C/C++ coding skills; familiarity with MATLAB

Preferred Skills:

• Experience with Audio related projects
• Communicating mechanical design, CAD

Compensation and Benefits