LiDAR Labeling Operations Policy & Quality Expert

Location: Remote

About Fuzu Atlas

Fuzu Atlas is a leading organisation at the forefront of transforming the intersection between artificial intelligence and human activities. We collaborate with top-tier professionals and prominent industry players to push the boundaries of AI innovation and lead advancements in this dynamic field. By joining Fuzu, you will become an integral part of a company that prioritises leadership, quality, and professional growth.

Position Overview

We are seeking a highly detail-oriented and technically strong Multi-Sensor LiDAR Labeling Operations Policy & Quality Expert to support labeling policy development, quality management, and operational excellence across autonomous vehicle (AV) data annotation programs. The role involves working with LiDAR, camera, radar, and sensor-fusion annotation workflows to define clear annotation standards, improve labeling quality, and support the development of high-quality datasets for autonomous driving systems.

Key Responsibilities

• Develop, maintain, and update annotation policies for 3D LiDAR object labeling, multi-sensor fusion, camera-LiDAR alignment, radar-assisted labeling, semantic segmentation, tracking, temporal consistency, and trajectory annotation.
  

• Define taxonomy, ontology, edge-case handling, and escalation guidelines.
  

• Translate perception model requirements into clear annotation specifications.
  

• Create annotation playbooks, SOPs, decision trees, and reviewer guidelines.
  

• Define quality metrics, acceptance criteria, and operational KPIs.
  

• Design and support QA processes, including golden tasks, reviewer calibration, and inter-annotator agreement.
  

• Conduct quality audits, identify recurring labeling issues, and drive corrective actions.
  

• Analyze annotation productivity, ambiguity trends, and policy gaps.
  

• Support workforce onboarding, certification, and calibration programs.
  

• Collaborate with labeling vendors and BPO partners to implement annotation policies.
  

• Work with perception, ML, tooling, and program teams to improve annotation quality and consistency.
  

• Support dataset launches, quality reviews, and continuous improvement initiatives.
  

Key Requirements

• Bachelor’s degree in Engineering, Computer Science, Robotics, Data Science, GIS, or a related field.
  

• 5+ years of experience in autonomous vehicle data annotation, LiDAR labeling operations, quality assurance, or annotation policy development.
  

• Strong understanding of 3D point cloud data, sensor fusion systems, object tracking, trajectory labeling, and AV perception pipelines.
  

• Experience working with annotation tools supporting LiDAR, multi-camera systems, radar, or HD maps.
  

• Proven experience managing annotation quality at scale.
  

• Strong analytical and problem-solving skills.
  

• Excellent documentation and stakeholder communication skills.
  

• Ability to work effectively with technical, operational, and vendor teams.
  

A must have to be considered:

• A working personal laptop (Please note this will be verified while shortlisting)
  

• An internet connection of 15 MBPS and above
  

• Applications will be reviewed on a rolling basis therefore the sooner you apply the better.