Responsibilities
- Contribute to the design and testing of SLAM and state estimation pipelines using LiDAR, IMU, and camera data
- Support the development and tuning of sensor fusion algorithms under guidance from the team
- Run evaluations in simulation and participate in field tests to analyze system performance
- Help identify and debug localization and mapping issues in collaboration with our other teams
Requirements
- Currently pursuing a Master’s degree in Robotics, Computer Science, or a related engineering field
- Solid understanding of robotics fundamentals, such as Kalman filtering, sensor fusion, feature extraction and matching, pose graph optimization, and 3D orientation representations (e.g. quaternions, Euler angles)
- Some hands-on experience with SLAM or state estimation systems, either through coursework, projects, or previous internships
- Familiarity with LiDAR, IMU, and camera data, and interest in fusing multi-sensor information for localization and mapping
- Proficient in C++ and Python, with good software engineering practices
- Fluent in English
Nice to Have
- Exposure to ROS1/ROS2 and experience debugging robotic systems is a plus
- Proficiency in additional languages is a plus
Work Arrangement
Remote (City/Region)
Additional Information
- Internship offers hands-on exposure to algorithm development, sensor fusion, and system integration
- Opportunities to validate work in real-world field tests
- Company values independent thinking combined with a collaborative spirit
- Each voice is important to move forward
- Encouragement to apply despite confidence gap or impostor syndrome
