Robotics Software Intern – Robotic Learning

Job Description

Internship, RL Engineer, Tesla AI (Fall 2026) | Tesla

The Tone:
This is an internship at Tesla, located on-site (specific city not mentioned in the listing). Tesla is committed to building humanoid bi-pedal robots at scale, making advancements in artificial intelligence and robotics a core focus. This role is critical as it involves designing and implementing reliable and efficient code for learned robotics, directly contributing to the development of precise manipulation and full-body locomotion capabilities in these advanced machines. Interns will experience their work repeatedly shipped to and utilized by thousands of humanoid robots in real-world applications, directly impacting the company’s ambitious goals.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: In-person, on-site (location not specified in listing)
• Pay: $100000–$150000 yearly
• Team: Software team, focused on designing and implementing reliable & efficient code for learned robotics for humanoid robots.
• Mission: To design, implement, and deploy reliable and efficient code for learned robotics, specifically for precise manipulation and full-body locomotion in humanoid robots.

What You’ll Actually Do
• Develop: Develop end-to-end robotic learning systems utilizing either reinforcement learning or imitation learning methodologies.
• Train: Train advanced machine learning and deep learning models on a centralized computing cluster, focusing on critical tasks such as grasping and full-body locomotion.
• Learn: Acquire proficiency in performing dexterous tasks, specifically using high degree of freedom robot hands for complex manipulations.
• Learn: Learn to implement and evaluate various robot policies designed to solve language-conditioned tasks, interpreting visual input for execution.

The Must-Haves
• Background: Currently pursuing an advanced academic degree (Master’s or Ph.D. level) in specialized fields such as Computer Science, Robotics, Machine Learning, or a closely related discipline, with an anticipated graduation date between 2026 and 2027. This program is for actively enrolled students, not recent graduates.
• Experience: Demonstrated prior experience in developing end-to-end robotic learning solutions, specifically applying either imitation learning or reinforcement learning techniques.
• Skills: Possess strong foundational knowledge in software development principles and core computing concepts.
• Bonus: Valuable exposure to robot learning paradigms that incorporate sensory data from tactile sensors and/or vision-based sensors.