Senior SLAM Engineer

Required Skills & Experience

• Masters or PhD in Robotics, Computer Science, Electrical Engineering, Computer Vision or a related field.
• 3+ years of SLAM, localization, mapping, robotics, or autonomous systems experience
• Strong software engineering skills in C++ or Python
• Deep understanding of visual SLAM, LiDAR SLAM, multi-session and multi-route SLAM.
• Strong hands-on SLAM localization experience
• Fleet-scale multi-route and/or multi-session SLAM experience
• Experience with camera, LiDAR, GNSS, IMU, and/or vehicle odometry data

Nice to Have Skills & Experience

• Understanding of VIO and multi-sensor localization
• Map generation and continuous map maintenance
• HD/lane-level mapping, map change detection, versioning, or map quality validation
• ROS/ROS2, OpenCV, Eigen
• Autonomous driving or ADAS experience

Job Description

Seeking a Senior SLAM Engineer to develop production-scale localization and mapping solutions for autonomous driving and ADAS. The role will focus heavily on SLAM localization and fleet-scale multi-route SLAM, leveraging repeated drives and multi-vehicle sensor data to improve localization accuracy and consistency.

Key Requirements

• Design and develop visual SLAM, LiDAR SLAM, VIO, multi-sensor localization, multi-session SLAM, and multi-route SLAM systems
• Develop fleet-scale multi-route SLAM algorithms that jointly optimize trajectories and observations across repeated routes, multiple vehicles, and large geographic areas
• Build scalable pose graph and bundle adjustment systems for globally consistent localization and mapping
• Develop loop closure, relocalization, place recognition, drift correction, and long-term landmark management capabilities
• Build multi-session map fusion and collaborative mapping solutions that account for changes in vehicles, lighting, seasons, weather, and road conditions
• Develop sensor-fusion frameworks using camera, LiDAR, GNSS, IMU, and vehicle odometry for localization and trajectory estimation
• Optimize SLAM, localization, and map optimization algorithms for large-scale cloud processing and production vehicle deployment