SLAM & Spatial Navigation Engineer (Robotics)

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Position Overview

We are looking for a SLAM & Spatial Navigation Engineer to develop real-time localization mapping and navigation systems for autonomous quadruped robots operating in complex environments including areas where GPS signals are unavailable or unreliable.

You will work on 3D LiDAR-based simultaneous localization and mapping (SLAM) sensor fusion and autonomous navigation using ROS 2. Your work will help robots understand their surroundings estimate their position build accurate maps and navigate uneven terrain while accounting for the movement and physical constraints of legged robotic platforms.

This role combines robotics perception spatial mapping localization and motion planning with a focus on reliable navigation in real-world indoor and outdoor environments.

Key Responsibilities

• Develop and optimize real-time 3D LiDAR-inertial odometry and mapping systems for GPS-denied indoor and outdoor environments.

• Implement and evaluate SLAM frameworks such as LIO-SAM Faster-LIO Cartographer or other suitable LiDAR-based mapping solutions.

• Process and analyze 3D point clouds using the Point Cloud Library (PCL) and related perception tools.

• Integrate LiDAR inertial measurement units (IMUs) and other relevant sensors to improve localization accuracy and mapping robustness.

• Configure integrate and tune ROS 2 navigation stacks including Nav2 for autonomous robotic navigation.

• Integrate semantic and topological costmaps from perception and AI systems to support environment-aware path planning.

• Develop sensor fusion and localization correction methods using available infrastructure references static camera anchors or known environmental markers.

• Design and optimize local path planners that account for quadruped robot dynamics uneven terrain and elevation maps.

• Generate and maintain terrain representations that support traversability analysis and safe navigation across complex surfaces.

• Evaluate localization drift mapping accuracy navigation performance and system reliability through simulation and real-world testing.

• Troubleshoot mapping and navigation failures optimize system performance and improve robustness under changing environmental conditions.

• Collaborate with robotics controls perception VLA and embedded systems engineers to integrate navigation capabilities into autonomous robotic platforms.

Qualifications

• Bachelors or Masters degree in Robotics Computer Science Electrical Engineering Mechanical Engineering or a related technical field.

• Approximately 46 years of relevant experience in SLAM robotics localization autonomous navigation or robotic perception.

• Strong programming skills in C and practical experience developing robotics software.

• Hands-on experience with 3D LiDAR-based SLAM and LiDAR-inertial odometry.

• Experience with one or more SLAM frameworks such as LIO-SAM Faster-LIO Cartographer or comparable solutions.

• Practical experience with ROS 2 and navigation frameworks such as Nav2.

• Familiarity with point cloud processing using PCL or similar libraries.

• Understanding of sensor fusion IMU integration localization drift correction and mapping optimization.

• Knowledge of GTSAM factor graphs pose-graph optimization or related estimation techniques is an advantage.

• Understanding of path planning costmaps terrain mapping and traversability analysis.

• Experience with quadruped robots legged robotics or navigation across uneven terrain is a plus.

• Strong analytical and debugging skills with the ability to validate algorithms in real-world robotic systems.

Why Join

• Work on advanced autonomous robotics and spatial navigation technologies.

• Develop mapping and localization systems for robots operating in challenging GPS-denied environments.

• Solve practical engineering problems involving 3D perception sensor fusion and autonomous navigation.

• Collaborate with multidisciplinary teams across robotics perception AI and motion control.

• Contribute to the development of intelligent robotic platforms designed for complex real-world environments.

Work Location & Arrangement

On-site at the robotics R&D facility in New Delhi India.