Autonomy Internship, Tesla Bot (Summer 2024)

We ask for a minimum of 12 weeks, full-time, for all Autopilot/Optimus internships. Please consider before submitting an application.

International Students: If your work authorization is through CPT, please consult your school before applying. You must be able to work 40 hours per week. Many students will be limited to part-time depending on their academic standing.

Internship Programs at Tesla

The Internship Recruiting Team is driven by the passion to recognize emerging talent. Our year-round program places the best students in positions that they will grow both technically and personally through their experience working closely with their Manager, Mentor, and team. We are dedicated to providing an experience that allows for the intern to experience life at Tesla by given them projects that are critical to their team’s success.

Locations

• Palo Alto, CA

About the Team

Tesla is on a path to build humanoid bi-pedal robots at scale. As a member of the software team, you will design and implement reliable & efficient code for classical or learned robotics, specifically applying to perception, callibration, locomotion, object manipulation and more. You will work on improving the robot’s behavior in the real world, and reflecting those capabilities in a simulation engine for evaluations and faster iterations. The code you will write will be deployed to our fleet of humanoid robots!

• Currentlyworking towards a BS, MS, or advanced degree in a relevant engineering programsuch as Robotics, Computer Science, Computer Engineering, MechanicalEngineering or Electrical Engineering.
• Graduating and/or able to join as a full-time member within 6 months of completing their academic requirements.
• Strong proficiency in C++ and Python.
• Experience with sensors, algorithms, and data structures relatedto localization and mapping (SLAM), obstacle avoidance, semantic segmentationand tracking, motion planning and trajectory optimization.
• Strong background in core robotics, including kinematic/dynamicmodeling, Bayesian state estimation (e.g., MAP, MMSE, MLE), 3D reconstruction,structure-from-motion, visual odometry, visual inertial odometry, bundleadjustment.
• Working knowledge of Git and Linux environments.