Robotics Engineering Intern — Hardware & Software
Hands-on robotics engineering internship at Trace Labs' Brooklyn research lab: build and operate robotic platforms (arms, dexterous hands, sensors), develop data collection/processing pipelines, and support robot learning and embodied AI experiments in simulation and on real hardware. Core stack: Python/C++, ROS, PyTorch/JAX, MuJoCo/Isaac Sim.
- Compensation
- $20–$50 / hr
- Location
- NYC
- Work setup
- Onsite
- Seniority
- Intern
- Employment
- Internship
- Experience
- Not specified
- Category
- Hardware
- Posted
Skills
Must have
- Currently pursuing a Bachelor's, Master's, or PhD in Robotics, CS, EE, ME, Computer Engineering, Mechatronics, or related field
- Solid programming skills in Python and/or C++ with experience developing, testing, or debugging software
- Foundational understanding of robotics concepts (kinematics, control, perception, sensing, system integration)
- Hands-on experience with robotics hardware, simulation, or substantial robotics software projects
- Strong practical problem-solving skills and ability to troubleshoot independently
- Good communication and collaboration skills and attention to technical detail
Nice to have
- Experience with robotic platforms (manipulators, dexterous hands, mobile or humanoid robots)
- Familiarity with ROS/ROS 2, motion planning, or robotic control software
- Experience with cameras, depth/tactile/force-torque sensors, motion capture, or multimodal sensor integration
- Experience with data acquisition, sensor calibration, temporal synchronization, or large-scale robotics datasets
- Familiarity with robot learning methods (imitation learning, reinforcement learning, diffusion policies, VLA models)
- Experience with ML frameworks such as PyTorch or JAX
- Experience with robotics simulation tools such as MuJoCo or Isaac Sim
- Experience with CAD, mechanical prototyping, 3D printing, electronics, or embedded systems
- Previous experience in an academic robotics lab, robotics competition, engineering internship, or independent project
- Contributions to open-source robotics software, datasets, or research publications
Full description
About Trace
Trace is building the data, infrastructure, and research that enable robots to learn from the real world. General-purpose robotics requires a deeper understanding of how robots learn from real-world data. Our research explores how to transform human experiences, including egocentric video, demonstrations, hand-object interactions, and multimodal sensory signals, into transferable representations, actionable knowledge, and generalizable robot behaviors. At our Brooklyn research lab, we combine fundamental research in robot learning, computer vision, and embodied AI with large-scale datasets, machine learning infrastructure, and real-world robotic experimentation. Our goal is to advance the science of robot learning while developing the datasets and learning foundations for increasingly capable, adaptable, and reliable robots.
About the role
We are looking for highly motivated and technically curious Robotics Engineering Interns to join our team in a hands-on hardware-and-software role, contributing to the development of robotic systems, data infrastructure, and experimental platforms that support cutting-edge research in robot learning and embodied AI. This internship is designed primarily for Master's and undergraduate students, although PhD students are also welcome to apply. We value practical robotics experience, strong engineering fundamentals, problem-solving ability, and a genuine interest in robotics research. Prior research publications are not required.
As a Robotics Engineering Intern, you will work closely with our research scientists, research interns, and engineers to build and operate robotic platforms, develop reliable data collection and processing pipelines, implement and evaluate learning-based robotic systems, and support experiments that connect human and robot data to downstream policy performance. You will have opportunities to take ownership of well-defined engineering and experimental projects, from hardware and software integration through implementation, testing, evaluation, and documentation. Depending on your background and interests, you may also contribute to research experiments, algorithm development, and technical publications. Our goal is to provide meaningful hands-on experience at the intersection of robotics engineering and robot learning research, while giving students opportunities to develop practical skills, deepen their research understanding, and contribute to advances in physical AI.
Projects you may work on
Depending on your experience and interests, your projects may involve one or more of the following areas:
- Robotic Hardware and System Integration
- Multimodal Data Collection and Infrastructure
- Data Processing, Calibration, and Quality Evaluation
- Human Demonstration and Robot Learning Systems