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Slam Engineer
4 months ago
Job overview
We are seeking a motivated SLAM Engineer to join our growing SLAM group. In this role, you will work closely with senior engineers to develop and optimize visual(-inertial) SLAM algorithms for our autonomous agricultural machinery. This position offers a unique opportunity to contribute to transformative projects in the field of autonomous systems and agricultural technology.
Responsibilities:
- Assist in the development and implementation of visual(-inertial) SLAM/odometry algorithms (both front- and back-ends).
- Work with sensor data (camera, IMU, LiDAR, radar) and tight/loose sensor fusion methods to develop robust pose estimation and mapping systems.
- Conduct experiments and field tests to validate SLAM solutions in real-world agricultural environments.
- Collaborate with senior engineers to integrate SLAM systems into the overall architecture of our autonomous machinery.
- Participate in code reviews, algorithm optimization, and system debugging.
- Document work clearly and thoroughly to support knowledge sharing and future development.
- Stay updated with the latest advancements in visual SLAM, online calibration systems, and related technologies.
Requirements:
- Bachelor’s degree or higher in Computer Science, Electrical Engineering, Robotics, or a related field.
- Understanding of SLAM/odometry concepts for front-ends (feature extraction, feature matching, optical flow, etc.) and back-ends (factor-graph/pose-graph optimization).
- Practical experience with SLAM systems deployed on autonomous machines (drones, vehicles, field robots).
- Understanding of mathematical concepts behind 3D vision.
- Experience with C++ and Python programming languages.
- Familiarity with ROS2 and its application in SLAM projects.
- Knowledge of sensor data processing, including cameras, IMUs, and LiDARs.
- Experience with software development tools such as Git, Docker, and CMake.
- Ability to work collaboratively in a team environment and communicate effectively.
- Some experience with software libraries such as GTSAM, G2O, OpenCV, PCL.
Nice to have
- First-author publications at top Computer Vision / Robotics conferences (CVPR, ICRA, ICCV, ECCV, IROS).
- Experience with deep-learning methods applied to SLAM.
- Familiarity with CUDA programming and optimization.
- Contributions to open-source SLAM or robotics projects
