About the job
We are seeking a Lead Robotics Engineer to own and grow our localization strategy across the autonomy stack. You will lead the localization team's technical direction, mentor engineers, and drive hiring — while remaining deeply hands-on with the core localization engine. This role is broad by design: rather than specializing in one sensor modality, you'll bring depth across LiDAR, GNSS/INS, visual, and sensor-fusion approaches, and know how to choose and combine the right one for the environment (open-road, GNSS-denied, indoor/structured, feature-sparse).
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Key Responsibilities
- Lead the technical roadmap for the localization stack, spanning sensor fusion, place recognition, mapping, and pose estimation — and set standards for architecture, testing, and code quality across the team.
- Design and implement state estimation pipelines (EKF/UKF, factor-graph/optimization-based) that fuse IMU, wheel odometry, GNSS/INS, LiDAR, and visual inputs for robust pose estimation in both structured and unstructured environments.
- Develop LiDAR-based localization and place-recognition methods (e.g., ScanContext, ICP, NDT, scan-matching against prior maps) for GNSS-denied or perceptually ambiguous environments (indoor, urban canyon, tunnels, parking structures).
- Implement and optimize graph-based and non-linear optimization solutions (Ceres, g2o, GTSAM) for global consistency, loop closure, and multi-sensor fusion.
- Design and implement VIO/visual-inertial localization algorithms where camera-based sensing is the appropriate modality, without treating it as the sole solution.
- Own hiring and technical interviewing for the localization team.
- Collaborate cross-functionally with perception, navigation, and controls teams.
- Stay current on state-of-the-art localization research, including differentiable optimization and learned approaches, and pragmatically evaluate where they add real value versus classical methods.
Qualifications
- Optimization: Strong background in differentiable optimization.
- State Estimation: Proven expertise in non-linear optimization (Ceres, g2o, GTSAM) and Bayesian filtering for autonomous navigation.
- 3D Geometry & Spatial Reasoning: Mastery of coordinate transformations, Lie groups/algebras (SO3, SE3), and 2D/3D geometry primitives.
- Map-Based Localization: Extensive experience in matching perception data to vectorized HD maps (Lanelet2, OpenDRIVE).
- Software Engineering: Expert-level Modern C++ (17/20) and Python, with a deep understanding of ROS 2 and performance-critical software design.
What we offer
We offer a competitive salary, a comprehensive benefits package, and the opportunity to work alongside some of the brightest minds in the Autonomous Robotics industry. Our work culture is collaborative and inclusive, with a strong focus on innovation and personal growth.
If you're passionate about advancing the frontiers of Autonomous Robotics and eager to leave a lasting mark in this domain, seize the opportunity and apply today to join us in sculpting the future of this dynamic field!
