Gatik · 2 days ago

Technical Lead, Mapping & Localization

Mountain View, CA

Full-time

Onsite

Senior Level

6+ years exp

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Artificial Intelligence (AI)Automotive

Growth Opportunities

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Responsibilities

Develop mapping algorithms and create a robust mapping pipeline that supports the building of high definition maps at large scale

Innovate in the area of localization, designing systems capable of centimeter-level accuracy using a blend of traditional and novel sensor fusion techniques, including but not limited to LIDAR, radar, cameras, and IMU data

Implement and optimize simultaneous localization and mapping (SLAM) algorithms for dynamic and large-scale environments, ensuring robust performance under diverse weather and lighting conditions

Lead the development of tools for map generation, simulation, and testing, enhancing the speed and efficiency of our mapping and localization pipeline

Work closely with the perception, planning, and control teams to ensure seamless integration of the mapping and localization subsystems within the autonomous driving stack

Analyze and architect safety and redundancy in the localization system

Own and drive highly visible performance metrics (e.g. latency, memory, bandwidth, power)

Author technical reports, patent applications, and academic papers, contributing to the company's intellectual property and research profile

Qualification

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C/C++PythonLinux environmentR&DAutonomous systemsRoboticsComputer visionPose estimationProbabilistic filteringBundle adjustmentNon-linear optimizationLarge-scale 3D dataSLAMGNSS/INSSensor calibrationData fusion algorithmsIntegration of sensorsLIDARRadarCamerasGeometric algorithmsProbabilistic algorithmsMappingLocalizationRobotics software developmentROSAutowareMachine learning frameworksTensorFlowPyTorch

Required

PhD in Computer Science, Electrical Engineering, Robotics, or a closely related field, with a focus on mapping, localization, or SLAM

Advanced proficiency in C/C++ and Python, with experience in developing high-performance algorithms in a Linux environment

Minimum of 6 years of experience in a research or R&D setting, with a proven track record in autonomous systems, robotics, or computer vision

Experience with pose estimation, probabilistic filtering, bundle adjustment, non-linear optimization, and large-scale 3D data

Expert-level knowledge of SLAM - frontend and backend, point cloud registration, GNSS/INS

Hands-on experience with sensor calibration, data fusion algorithms, and the integration of various sensors (e.g., LIDAR, radar, cameras) for vehicle localization

Deep understanding of geometric and probabilistic algorithms for mapping and localization, and familiarity with the latest research and trends in the field

Demonstrated experience with robotics software development tools such as ROS, Autoware, or similar, and familiarity with machine learning frameworks like TensorFlow or PyTorch

Research background in SLAM and/or publications in localization and mapping applications