Internship, Reinforcement Learning Engineer, Optimus (Summer 2026)

Consider before submitting an application: This position is expected to start around August or September 2025 and continue through the Fall term (ending approximately December 2025) or continuing into Winter/Spring 2026 if available and there is an opportunity to do so. We ask for a minimum of 12 weeks, full-time 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. 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 learned robotics, specifically applying to precise manipulation, full body locomotion, and more. You will be responsible for end-to-end robotic learning and own this stack from inception to deployment. Most importantly, you will see your work repeatedly shipped to and utilized by thousands of humanoid robots in real world applications.

Responsibilities

Develop end-to-end robotic learning with either reinforcement or imitation learning Train machine learning and deep learning models on a computing cluster for grasping and locomotion tasks Learn to perform dexterous tasks using high degree of freedom hands Learn different robot policies to solve language-conditioned tasks from vision

Requirements

Currently pursuing an advanced degree in Computer Science, Robotics, Machine Learning, or a related field with a gradation date between 2025 - 2026 Experience in end-to-end robotic learning, with either imitation or reinforcement learning Exposure to robot learning through tactile and/or vision-based sensors is a plus Strong software and computing fundamentals