Internship

Job Description

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 robots at scale to automate repetitive and boring tasks. The goal of our reinforcement learning team is to build and demonstrate a general robot learning system that can leverage AI to perform complex physical tasks, ranging from full body locomotion, precise manipulation, and more. Our reinforcement and imitation learning engineers are 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. 

Job Responsibilities

• Develop end-to-end robotic learning with either reinforcement or imitation learning 
• Reinforcing correct set of actions, rewarding correct behavior and negating incorrect behavior (with real-time action/reward feedback loops) 
• Perform a large number of instructions and generalize new tasks with different objects and environments 
• Learn to perform dexterous tasks using high degree of freedom hands
• Learn different robot policies to solve language-conditioned tasks from vision 
• Ship production quality, safety-critical software 

Job Requirements

• Experience in end-to-end robotic learning, with either imitation or reinforcement learning 
• Experience writing production-level Python (including Numpy and Pytorch) 
• Experience with distributed deep learning systems 
• Exposure to robot learning through tactile and/or vision-based sensors is a plus 
• Proven track record of training and deploying real world neural networks
• Currently pursuing a degree in a related field of study with a graduation date between December 2025 – May 2026