3 months ago
Remote, United States or Seattle, WA, USASenior
Base Salary
$165k - $215k/yr
Responsibilities
- Architect and develop robust multi-sensor fusion algorithms for real-time state estimation using LiDAR, IMU, GNSS, wheel odometry, and kinematics.
- Advance mapping capabilities including point-cloud registration, loop closure, dynamic map updates, alignment, and fleet-wide map distribution.
- Build automated intrinsic, extrinsic, and spatio-temporal calibration pipelines for complex multi-sensor rigs.
- Implement and optimize graph- or filter-based localization algorithms for deployment on edge hardware.
- Integrate SLAM outputs with perception, planning, controls, machine operations, and safety systems.
- Analyze field telemetry, logs, drift, loop-closure failures, edge cases, and failure modes to improve system reliability.
- Collaborate with field engineers and operators to validate localization performance on active jobsites.
Requirements
- Bachelor’s or master’s degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or a related field.
- At least 5 years of professional experience building SLAM, state-estimation, or localization systems.
- Strong mathematical foundation in 3D geometry, linear algebra, probabilistic robotics, kinematics, and optimization.
- Deep expertise in Extended/Unscented Kalman Filters, Particle Filters, and optimization frameworks such as GTSAM, Ceres Solver, or g2o.
- Hands-on experience developing automated multi-sensor calibration pipelines for LiDAR, cameras, IMUs, and GNSS.
- Exceptional programming ability in modern C++ and Python.
- Experience with LiDAR odometry and mapping, LOAM variants, ICP, NDT, and large 3D point clouds.
- Experience tightly coupling IMU data with LiDAR, visual, or GNSS measurements.
- Experience debugging complex real-world robotic systems using data, logs, and performance metrics.
- Experience working in robotics.
- Preferred: experience with off-road autonomous vehicles, agriculture, mining, heavy machinery, continuous or online calibration, complex vehicle kinematics, severe wheel or track slip, and map obsolescence in dynamic environments.
