Key Responsibilities:
Perform 3D LiDAR point cloud annotation by fitting accurate 3D cuboids around vehicles, pedestrians, cyclists, and static structures across frame sequences.
Perform 3D semantic segmentation by accurately labeling individual points within dense point clouds without gaps or overlaps.
Review, refine, and audit AI-generated 3D bounding boxes and multi-sensor alignments involving LiDAR and 2D camera feeds.
Track energetic objects across multiple frames while maintaining consistency in pitch, roll, yaw, and heading vectors.
Follow defined annotation guidelines for cuboid boundaries, point density, occlusion handling, and spatial accuracy.
Maintain required quality benchmarks while completing assigned annotation tasks within defined productivity targets.
Use software shortcuts and hotkeys efficiently while working on 3D annotation workflows.

Key Requirements:




Minimum 1+ year of hands-on experience in 3D LiDAR point cloud annotation, 3D segmentation, or multi-sensor data labeling
Experience with platforms such as Segments.ai, BasicAI, Cognic, Scale AI, CVAT, or equivalent 3D annotation tools
Ability to maintain 95%+ annotation accuracy
Robust understanding of 3D spatial geometry, object boundaries, segmentation, and occlusion handling
Ability to identify and annotate only visually verifiable spatial information without assumptions
Valuable knowledge of object tracking across multi-frame LiDAR sequences
Ability to work efficiently using keyboard shortcuts and hotkeys
Comfortable working with background screen-recording requirements

Location - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune,Remote

📌 Lidar 3d Annotation & Data Labeling Specialist Mumbai
🏢 QASolvers
📍 Mumbai