Posted:
2/11/2026, 1:59:30 PM
Location(s):
New York, New York, United States ⋅ New York, United States
Experience Level(s):
Internship
Field(s):
AI & Machine Learning ⋅ Mechanical Engineering
About Tuesday
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 Manipulation Internship
We are seeking a talented graduate student for our Manipulation Internship Program to help us bring our robots to life. Over the 12+ weeks you’ll spend with us, you will be responsible for improving and deploying interpretable robot policies by blending classical robotics with large models for perception and planning.
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 large-scale AI and real-world, helpful, and delightful robot behavior. If you have ever fine-tuned an open-source model to make a robot arm make you a cup of coffee in the morning just because you could, you are exactly who we're looking for.
Responsibilities:
Deploy and benchmark large computer vision, language, and policy models.
Implement research papers spanning both classical and learned approaches to robotic control and perception.
Propose and evaluate ideas for our autonomy stack in collaboration with our manipulation team.
Required Qualifications:
Academic status: currently enrolled in a graduate-level (MS or PhD) computer science or robotics degree program.
ML Skillset: Proven experience fine-tuning robot policies, or computer vision models specifically in the domain of robotic manipulation.
Robotics Skillset: Hands-on experience deploying models onto real-world robots. 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 imitation learning, diffusion policies, or other modern manipulation-focused models.
Familiarity with on-device optimization (e.g., TensorRT, quantization, pruning).
Experience with data collection at scale, especially using teleoperation.
About You:
Technical Excellence: Deep knowledge of modern ML and robotics with a demonstrated ability to design, implement, test, and iterate quickly.
Product Focus: You believe in home robotics and will do whatever it takes to make the robot's behaviors reliable and delightful for our customers.
If you don’t have these qualifications, but you really want to do this job, you should apply for it anyway. This is a startup: passion and work ethic count for a lot.
What Tuesday Offers:
The opportunity to play a critical role in developing the future of home robotics. You will be building an important piece of infrastructure and your design decisions will make the difference between a delightful companion and a dysfunctional boondoggle.
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.
Fraud Alert: Please look out for scams and bad actors. We will only ever email you from the email domain @tuesdaylab.com, and we will never ask for payment or sensitive info over email.
Website: https://www.tuesdaylab.com/
Headquarter Location: New York, United States
Employee Count: 1-10
Year Founded: 2023
IPO Status: Private
Last Funding Type: Seed
Industries: Robotics