Staff Autonomy Engineer - Localization

The Autonomy Mapping & Localization group's mission is to provide our vehicles with world-class spatial intelligence, semantic and topological mapping, and state estimation to model and navigate complex urban, suburban, and rural environments. We are looking for a Staff Autonomy Engineer to join our team and architect the next generation of our mapping and localization stack. As the Staff Autonomy Engineer for Localization, you will be at the forefront of this mission, building the production-grade multimodal localization foundation that allows our vehicles to navigate the world's most challenging roads at scale.

• →Architect and lead the development of a production-grade, multimodal localization stack, integrating Cameras, LiDAR, Radar, GNSS, and IMU data to ensure centimeter-level accuracy and high availability.
• →Design and implement advanced state estimation frameworks, such as Factor Graphs or sliding-window optimization (e.g., GTSAM, Ceres), optimized for real-time performance and robustness against sensor degradation and across diverse Operational Design Domains (ODDs).
• →Own the localization integrity and safety strategy. Develop sophisticated uncertainty estimation and fault detection, isolation, and recovery (FDIR) mechanisms to meet stringent safety requirements.
• →Drive technical roadmaps for next-generation localization techniques, including map and sparse landmark-based localization (Vision/LiDAR/Radar), visual-inertial odometry (VIO), and wheel-inertial odometry.
• →Lead cross-functional system integration, developing software and system requirements while defining technical interfaces and performance contracts (e.g., state estimation and uncertainty bounds) between Localization and upstream and downstream modules like Perception, Behavior, Policy, and Prediction.
• →Establish rigorous evaluation frameworks and metrics for localization performance, including pose accuracy, temporal consistency, and system-level reliability across diverse ODDs.
• →Spearhead major feature development including high-level architecture design, code reviews, issue diagnosis, and technical resolution.
• →Provide high-level technical mentorship to senior and junior engineers, conducting deep-dive design and code reviews and fostering a culture of engineering excellence and rigorous validation.
• →Stay at the research frontier, evaluating and adapting cutting-edge techniques in SLAM, deep-learned localization features, and large-scale map-matching to deliver production-ready solutions.

Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:

• Ph.D. or Master’s degree in Robotics, Computer Science, Electrical Engineering, or a related field with a deep mathematical foundation in state estimation.
• 10+ years of industry experience developing and deploying high-performance localization or state estimation systems for autonomous robots or vehicles, with at least 5 years in a lead/staff/principal technical role.
• Expertise in modern state estimation techniques: Deep understanding of probabilistic robotics, Factor Graphs or sliding-window optimization (e.g., GTSAM, Ceres), and Kalman filtering.
• Advanced Sensor Fusion: Proven track record of fusing disparate data sources including Cameras (Visual Odometry), LiDAR (ICP/NDT), Radar, IMU, and GNSS.
• Strong C++ Programming: Mastery of modern C++ (14/17/20) in a Linux environment, with a focus on real-time constraints, multi-threading, and performance optimization.
• System Architecture: Experience designing modular, testable software architectures for safety-critical systems.
• Leadership: Demonstrated ability to drive technical roadmaps and architectural standards while mentoring senior engineers from inception to fleet-wide deployment.

• 12+ years of industry experience developing and deploying high-performance localization or state estimation systems, including success navigating the full product lifecycle from R&D to commercial scale-up.
• Experience with SLAM (Simultaneous Localization and Mapping) for large-scale urban, suburban, and rural environments.
• Experience with deep-learning based localization features or neural state estimation.
• Expertise in vehicle dynamics modeling and wheel odometry calibration.
• A proven record of technical leadership, inventions (patents), or publications in top-tier robotics conferences (e.g., ICRA, IROS, RSS).

• Standard office working conditions which includes but is not limited to:
• Prolonged sitting
• Prolonged standing
• Prolonged computer use