About Bonsai Robotics

Bonsai Robotics' mission is to create the next leap forward in agriculture equipment efficiency by creating a new ecosystem of semi-autonomous robotic machinery. Orchards are dusty, hazard-filled, and GPS-denied. The GPS-based autosteer features that have driven row crop efficiencies cannot function in orchards. Our vision, AI, and machine control systems offer human-level environment understanding and local navigation capabilities and will be the platform for a new wave of innovation in agricultural production and management systems. Our state-of-the-art technology empowers orchard managers to optimize their operations, dramatically reduce operational expenses, and increase profitability. 

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, Ceres, 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.