Sensor Calibration & Integration Intern
Compensation
Salary undisclosedDescription
Join our team to build a seamless, user-friendly calibration suite for multi-modal sensor systems, encompassing RGB cameras, LiDARs, and IMUs. This is an exciting opportunity to have a direct real-world impact by enabling high-quality robotics research through precise sensor integration. You will work on the foundational tools that allow our intelligent machines to perceive and interact with the world accurately.
We are looking for Master or PhD students to work full-time for an extended period (~6 months) in an environment where researchers and engineers are developing state-of-the-art robotics technology. If you are interested in building tools that enable cutting edge robot research we encourage you to apply.
What You'll Do
Play a key role in developing a seamless, user-friendly calibration suite for our multi-modal sensor systems, including RGB cameras, LiDARs, and IMUs.
Work collaboratively with researchers focused on providing a solid foundation for building advanced robotic systems.
Provide solutions to complex problems targeting robots deployed in the real world.
Design complex systems and make them easy to use.
Apply classical optimization as well as learning algorithms to practical robotics problems.
What You'll Need
Master or PhD student in robotics, computer vision, or a related field.
Proficiency in C++ and Python is a must.
Solid understanding of state estimation and optimization techniques.
Familiarity with factor graph optimization, ideally including experience with GTSAM.
Interest in building robust tools that support robotics research.
Areas of Special Interest
Experience with learning-based calibration techniques.
Open source projects that showcase your problem solving skills, ideally in the field of robotics, computer vision or a related field.
Track record of publications in top-tier conferences and journals in Machine Learning, Robotics, or related fields is a plus
(e.g. CVPR, ICCV, ECCV, TPAMI, IJCV, NIPS, ICLR, ICML, IJRR, RSS, ICRA, IROS etc.)
Stack
- Posted
- Aug 31, 2026
- Last seen
- Sep 2, 2026
- First seen
- Sep 2, 2026
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