LiDAR 3D Annotation & Data Labeling Specialist

📋 Description

• Create accurate 3D bounding boxes around vehicles, pedestrians, cyclists, static structures, and
• Perform detailed 3D semantic segmentation by labeling individual points within dense point clouds
• Review and refine AI-generated 3D annotations to ensure they meet established spatial accuracy and
• Conduct multi-sensor quality assurance by validating LiDAR annotations against 2D camera feeds and
• Track dynamic objects consistently across multiple LiDAR frames, maintaining accurate pitch, roll
• Apply strict cuboid boundary, point-density, occlusion, and spatial annotation guidelines

🎯 Requirements

• At least 6 months of hands-on experience with 3D LiDAR point cloud annotation, 3D semantic
• Demonstrated proficiency with 3D annotation and spatial-data platforms such as Segments.ai
• Strong understanding of 3D spatial geometry and the ability to interpret point-cloud data
• Proven ability to maintain high annotation accuracy, with experience working toward or achieving
• Familiarity with 3D bounding boxes, object tracking, occlusion handling, spatial segmentation, and
• Ability to accurately interpret object orientation and maintain consistency across pitch, roll

🎁 Benefits

• Long-term contract opportunities with an expected workload of 25–40 hours per week.
• Ongoing paid project batches following successful certification.
• Paid onboarding and certification process, with approximately one hour of onboarding paid upon
• Structured training covering spatial annotation guidelines, workflows, and productivity shortcuts.
• Opportunity to work on advanced AI, autonomous vehicle, and spatial intelligence projects.
• High-performing contributors may receive priority access to more advanced and higher-paying