Multi-Sensor LiDAR Labeling Operations Policy and Quality Expert

About the Role

Join a pioneering organisation dedicated to advancing the fusion of artificial intelligence and human endeavor, collaborating with leading industry experts and professionals to drive innovation in AI technology. This position offers the opportunity to contribute meaningfully within a company devoted to leadership, quality, and continuous professional development.

Position Summary

We are looking for a meticulous and technically proficient expert to lead the development and management of annotation policies, quality assurance, and operational excellence in data annotation projects for autonomous vehicles. This role focuses on workflows involving LiDAR, camera, radar, and sensor fusion, aiming to establish precise annotation standards and enhance dataset accuracy for autonomous driving applications.

Key Responsibilities

• Develop, regularly update, and maintain annotation guidelines for 3D LiDAR object labeling, multi-sensor fusion, camera-LiDAR calibration, radar-assisted annotations, semantic segmentation, object tracking, temporal consistency, and trajectory annotation.
• Define comprehensive taxonomy, ontology frameworks, procedures for handling edge cases, and escalation protocols.
• Interpret perception model requirements into explicit annotation instructions.
• Create detailed annotation manuals, standard operating procedures, decision trees, and reviewer guidance documents.
• Establish quality metrics, acceptance standards, and operational key performance indicators.
• Design and oversee quality assurance processes including golden tasks, reviewer calibration sessions, and measurement of inter-annotator reliability.
• Perform quality audits, identify recurrent labeling problems, and lead initiatives for corrective measures.
• Analyze productivity and ambiguity trends in annotations and address policy deficiencies.
• Support onboarding, certification, and calibration training programs for annotation staff.
• Collaborate closely with labeling vendors and BPO partners to ensure consistent application of annotation policies.
• Partner with perception, machine learning, tooling, and program teams to enhance annotation consistency and quality.
• Assist in dataset launches, quality control reviews, and ongoing refinement practices.

Essential Requirements

• Bachelor’s degree in Engineering, Computer Science, Robotics, Data Science, GIS, or related disciplines.
• Minimum of five years' experience in autonomous vehicle data annotation, LiDAR labeling operations, quality management, or policy creation.
• In-depth knowledge of 3D point cloud data, sensor fusion frameworks, object tracking methodologies, trajectory labeling, and autonomous vehicle perception workflows.
• Experience with annotation platforms supporting LiDAR, multi-camera arrays, radar, or high-definition mapping systems.
• Proven expertise in overseeing large-scale annotation quality assurance processes.
• Strong analytical thinking and problem-solving abilities.
• Exceptional documentation skills and capacity to communicate with diverse stakeholders.
• Capability to collaborate effectively with technical teams, operational staff, and external vendors.
• Possession of a personal laptop and stable internet bandwidth of at least 15 Mbps is mandatory (verification during shortlisting applies).

Additional Notes

Applications are evaluated continuously; early submission is encouraged.