Staff Autonomy Engineer - Localization
New
M
May MobilityAutonomous Vehicles
Remote, USAFull-TimeStaff
Salary235,000 - 285,000 USD per year
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Job Details
- Experience
- 10+ years of industry experience; 12+ years desirable.
- Required Skills
- C++LinuxComputer Vision
Requirements
- 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.
- At least 5 years of experience in a lead, staff, or principal technical role.
- Expertise in modern state estimation techniques, including probabilistic robotics, Factor Graphs or sliding-window optimization (e.g., GTSAM, Ceres), and Kalman filtering.
- Advanced Sensor Fusion experience with Cameras (Visual Odometry), LiDAR (ICP/NDT), Radar, IMU, and GNSS.
- Mastery of modern C++ (14/17/20) in a Linux environment, with a focus on real-time constraints, multi-threading, and performance optimization.
- Experience designing modular, testable software architectures for safety-critical systems.
- Demonstrated ability to drive technical roadmaps and architectural standards while mentoring senior engineers.
Responsibilities
- 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.
- Own the localization integrity and safety strategy, developing sophisticated uncertainty estimation and fault detection, isolation, and recovery (FDIR) mechanisms.
- Drive technical roadmaps for next-generation localization techniques, including map and sparse landmark-based localization, visual-inertial odometry (VIO), and wheel-inertial odometry.
- Lead cross-functional system integration, developing software requirements and defining technical interfaces between localization and upstream/downstream modules.
- Establish rigorous evaluation frameworks and metrics for localization performance, including pose accuracy, temporal consistency, and system-level reliability.
- Provide high-level technical mentorship to senior and junior engineers through design and code reviews.
- Stay at the research frontier, evaluating and adapting cutting-edge techniques in SLAM, deep-learned localization features, and large-scale map-matching.
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