Senior Robotics Navigation Engineer

Job description

Job responsibilities

• Design, implement, and deploy production-grade 3D SLAM and localization systems fusing data from LiDAR, RGB-D cameras, IMUs, wheel encoders, and proprioceptive signals
• Build and maintain state estimation pipelines — Kalman Filters, Extended Kalman Filters (EKF), Unscented Kalman Filters (UKF), or Factor Graph backends (GTSAM, Ceres, g2o) — with reliable accuracy in dynamic,…
• Develop real-time 3D navigation algorithms: costmap generation from point clouds, global and local path planners (sampling-based, optimization-based), and traversability analysis
• Implement sensor calibration pipelines (intrinsic and extrinsic) for multi-sensor rigs; own the calibration quality that underpins system accuracy
• Design and build the evaluation and regression frameworks that prove the navigation stack is working correctly — logging, metrics, replay tooling, and failure analysis infrastructure
• Collaborate with perception, controls, and hardware teams to integrate the navigation stack end-to-end into the full robot autonomy system
• Troubleshoot and resolve challenging field failures; own root cause analysis and system-level fixes when localization or navigation breaks in deployment
• Mentor junior engineers and contribute to technical roadmap planning for the autonomy stack

Job requirements

• 5+ years of industry experience in robotics autonomy, with a primary focus on SLAM, localization, or state estimation
• Proven track record of deploying navigation or SLAM systems on real autonomous platforms — self-driving vehicles, AGVs, mobile robots, or equivalent — not just simulation or research prototypes
• Deep theoretical and practical command of probabilistic robotics: Bayesian filtering, sensor fusion, covariance modeling, and non-linear optimization
• Hands-on experience with 3D SLAM modalities: LiDAR SLAM, Visual SLAM (VSLAM), Visual-Inertial Odometry (VIO), or multi-modal fusion
• Proficiency in C++ (C++14/17 or newer) for real-time, performance-critical code; strong software engineering fundamentals
• Experience with optimization libraries: GTSAM, Ceres Solver, g2o, or equivalent factor graph backends
• Familiarity with ROS/ROS 2 and standard robotics tooling
• Ability to explain why a localization module failed in a specific scenario to both a technical peer and a non-technical stakeholder