Data Labeler – Autonomous Vehicle & ADAS (Nairobi)

About the role

Digital Divide Data is offering a 2‑week, in‑person boot camp for experienced data annotation professionals to work on autonomous vehicle (AV) and advanced driver‑assistance systems (ADAS) projects. Candidates will receive intensive training and, upon successful completion, may be placed on production projects.

Key responsibilities

• Perform LiDAR and point‑cloud annotation, including 2D and 3D bounding boxes.
• Annotate images and video for object detection, classification, tracking, and segmentation (polygon, semantic, instance).
• Label lanes, roads, pedestrians, vehicles and environmental features.
• Conduct quality assurance for AV and ADAS datasets and follow detailed annotation guidelines.

Required profile

• Minimum 1 year of hands‑on experience in AV, ADAS or related data annotation.
• Strong understanding of annotation quality standards and ability to meet productivity and quality targets.
• Excellent attention to detail, able to work accurately on repetitive and complex tasks.
• Available for on‑site work in Nairobi and not currently enrolled as a student.

Required skills

• LiDAR point‑cloud annotation.
• 2D and 3D bounding‑box creation.
• Image and video annotation.
• Object detection, classification and tracking.
• Polygon, semantic and instance segmentation.
• Lane, road, pedestrian, vehicle and environmental feature labeling.
• AV/ADAS quality assurance.
• Transcription, captioning and prompt‑response writing.