About the role
Key Responsibilities
- Integrate RGB/RGB-D cameras, depth sensors, IMUs, 6DoF trackers, and robotic/handheld grippers into data collection rigs.
- Configure and validate multi-sensor systems for synchronized data capture.
- Perform camera calibration, sensor calibration, and coordinate-frame alignment.
- Configure and maintain ROS/ROS2 pipelines for sensor integration and data collection.
- Implement and maintain data logging workflows using ROS bags, MCAP, or similar formats.
- Develop tools and scripts in Python and/or C++ for system integration, testing, and data validation.
- Troubleshoot hardware, software, networking, and synchronization issues across the collection setup.
- Validate sensor data quality, timestamps, coordinate transforms, and system performance.
- Develop repeatable data collection and validation workflows for robotics and embodied AI datasets.
- Document system configurations, calibration procedures, troubleshooting steps, and collection protocols.
- Collaborate with robotics, computer vision, and data collection teams to improve the reliability and scalability of the lab setup.
Required Qualifications
- Professional experience with robotics, computer vision, sensor integration, or related engineering fields.
- Strong programming skills in Python and/or C++.
- Hands-on experience with ROS or ROS2.
- Experience working with RGB/RGB-D cameras and depth sensors.
- Understanding of camera calibration and coordinate transformations.
- Experience with IMUs and/or 6DoF tracking systems.
- Comfortable working in a Linux environment.
- Experience with Git and standard software development workflows.
- Strong troubleshooting and problem-solving skills.
- Ability to work hands-on with both hardware and software.
- Basic understanding of SLAM, VIO, or related localization/visual tracking concepts.
Nice to Have
Experience with any of the following will be considered a strong advantage:
- OAK-D
- Intel RealSense
- ZED cameras
- VIVE / SteamVR / OpenXR
- MCAP
- Robotics data collection platforms or datasets
- Robotic manipulators or grippers
- Multi-camera synchronization
- Hand tracking or motion capture systems
- SLAM/VIO pipelines
- Experience with embodied AI, robot learning, or manipulation datasets
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