Robotics Engineering Intern — Hardware & Software

The role

Robotics Engineering Interns will build and operate robotic platforms and develop data collection and processing pipelines. They will support research in robot learning and embodied AI through hardware and software integration.

What you will do

• Build and integrate robotic systems including robot arms, dexterous hands, sensors, and cameras.
• Develop and maintain robotics software and data pipelines.
• Support robot learning research experiments by implementing methods and preparing datasets.
• Design and execute systematic tests to assess hardware and software performance.
• Debug and troubleshoot complex robotic systems.
• Analyze experimental results and failure cases.
• Collaborate with researchers and engineers to improve workflows and prototype capabilities.
• Document implementations, experimental procedures, and results.

Required qualifications

• Currently pursuing a Bachelor's, Master's, or PhD degree in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, Computer Engineering, Mechatronics, or a closely related field.
• Solid programming skills in Python and/or C++.
• Experience developing, testing, or debugging software for robotics, machine learning, or related technical applications.
• Foundational understanding of robotics concepts such as robot kinematics, control, perception, sensing, or robotic system integration.
• Hands-on experience with robotics hardware, simulation, or substantial robotics software projects.
• Strong practical problem-solving skills.
• Good communication and collaboration skills.

Nice to have

• Experience with robotic platforms such as manipulators, dexterous hands, mobile robots, or humanoid robots.
• Familiarity with ROS/ROS 2, robot communication interfaces, motion planning, or robotic control software.
• Experience with cameras, depth sensors, tactile sensors, force/torque sensors, motion capture systems, or multimodal sensor integration.
• Experience with data acquisition, sensor calibration, temporal synchronization, data processing, or large-scale robotics datasets.
• Familiarity with robot learning methods such as imitation learning, reinforcement learning, diffusion policies, or vision-language-action models.
• Experience with machine learning frameworks such as PyTorch or JAX.
• Experience with robotics simulation tools such as MuJoCo, Isaac Sim, or related environments.
• Experience with CAD, mechanical prototyping, 3D printing, electronics, or embedded systems.
• Previous experience in an academic robotics lab, robotics competition, engineering internship, or substantial independent robotics project.
• Contributions to open-source robotics software, technical projects, datasets, or research publications.

Benefits

• Academic credit may be available if required by your degree program.

Before you apply

• Submit resume/CV along with 1-3 examples of relevant technical or research work.
• Indicate interest in summer internship, part-time internship, or full-time co-op.

About the company

Trace is building the data, infrastructure, and research that enable robots to learn from the real world. Their Brooklyn research lab combines fundamental research in robot learning, computer vision, and embodied AI.