Locomotion Co-Op/Internship (Summer 2026)

Tuesday Lab • New York, NY

13d

About The Position

Tuesday Lab builds delightful robots. We are driven by a desire to make everyday life easier and more fun through cutting-edge robotics. If you love watching videos of robots helping out around the house, deploy new policies onto your lab’s robot just to see how they do, and take inspiration from sci-fi rather than real life, you should come work at the Lab. We are engineers, researchers, and builders who love living among our creations. Our mission is to make the magical world of animated objects accessible to everyone. Graduate Student Locomotion Co-Op/Internship We are seeking a talented graduate student for our Locomotion Co-Op program to help us bring our robots to life. Over the 15-20 weeks you’ll spend with us, you will be responsible for fine-tuning bipedal locomotion policies and deploying them onto our physical robot hardware. This is a high-impact, hands-on role for someone who loves seeing their models actually work on a physical system, not just in simulation. You will be critical in bridging the gap between bleeding edge robotics research and real-world, helpful, and delightful robot behavior. If you have ever tried to make your lab robot do a backflip because you were bored on a Friday night, this is the role for you!

Requirements

• Academic status: currently enrolled in a graduate-level (MS or PhD) computer science or robotics degree program.
• ML Skillset: Proven experience training robotic locomotion policy models from scratch on new hardware. Hands-on experience deploying models onto real-world robots.
• Robotics Skillset: Familiarity with robotics middleware (like ROS/ROS2) and the challenges of working with physical hardware (sensors, actuators).
• A portfolio of projects (e.g., from GitHub, a personal blog, or academic papers) demonstrating hands-on robotics and ML integration.

Nice To Haves

• Experience specifically with training bipedal locomotion policies, especially in IsaacSim/IsaacLab
• Experience with generating physically realistic but expressive motion using character control techniques

Responsibilities

• Train robot policy models for naturalistic walking using techniques like DeepMimic or AMP to achieve robust locomotion and expressive emotes.
• Iterate on model performance and training environment to bridge the sim2real gap with our custom hardware
• Test and validate model performance on the physical robot, troubleshooting issues that span from the model's "understanding" to its physical execution.
• Collaborate with our hardware and software teams to integrate the ML-driven behaviors into the robot's autonomy stack.

Benefits

• The opportunity to play a critical role in developing the future of home robotics. You will be contributing to our robot’s most important behaviors and your design decisions will make the difference between a useful robot and a dangerous one.
• Work alongside people with deep expertise who love playful applications and are excited about building the future.
• Freedom to rapidly iterate, contribute to the technical direction of the company, and contribute novel and impactful solutions to important problems in robotics.

What This Job Offers

• Career Level: Intern