Data Labelers- AV/ADAS at Digital Divide Data (DDD Kenya)

Hiring: NairobiCity Newsroom
Stare
Open
Source
MyJobMag
• Job Type Contract , Full Time
• Qualification BA/BSc/HND
• Experience 1 year
• Location Nairobi
• Job Field Data, Business Analysis and AI , ICT / Computer
• LiDAR and point-cloud annotation.
• 2D and 3D bounding boxes.
• Image and video annotation.
• Object detection, classification, and tracking.
• Polygon, semantic, or instance segmentation.
• Lane, road, pedestrian, vehicle, and environmental feature annotation.
• Autonomous Vehicle or ADAS quality assurance.
• Interpretation and application of detailed annotation guidelines.
• Language-based tasks like transcription, captioning, and prompt-response writing
• Have 1+ years of hands-on experience in Autonomous Vehicle, ADAS, or closely related data annotation work.
• Demonstrate a strong understanding of annotation quality standards and guidelines.
• Have excellent attention to detail and the ability to work accurately on repetitive and complex tasks.
• Be able to meet defined productivity and quality expectations.
• Be available for potential project deployment after successfully completing the assessment process.
• Be willing to complete experience verification and a practical skills assessment.
• Reading and writing proficiency in English
• The Training will be a 2-week, 80-hour in-person boot camp combining theory, practical exercises, and daily skill checks.
• AV fundamentals: Scene understanding, object classification, LiDAR/point clouds, 3D annotation, precision, and 2D/3D correlation.
• Driving and temporal reasoning: Tracking over time, ego behaviour, traffic and road context, agent interaction, and spatio-temporal reasoning.
• Advanced reasoning: Logical linking, causal/VLA reasoning, and working with evidence and uncertainty.
• Quality and adaptability: Attention to detail, learning agility, adapting to changing guidelines, and independent QA.
• Hands-on application: Learners apply concepts through practical annotation tasks, calibration, feedback, and exercises, not classroom learning alone.
• Post-Training assessment: Five evaluation tasks combining tool-based scoring and expert review, with critical gates for technical execution, reasoning, quality, and adaptability.
• Production readiness: Trainees who meet the required standard move into production as project opportunities become available
• Job Type Contract , Full Time • Qualification BA/BSc/HND • Experience 1 year • Location Nairobi • Job Field Data, Business Analysis and AI , ICT / Computer • LiDAR and point-cloud annotation. • 2D and 3D bounding boxes. • Image and video annotation. • Object detection, classification, and tracking. • Polygon, semantic, or instance segmentation. • Lane, road, pedestrian, vehicle, and environmental feature annotation. • Autonomous Vehicle or ADAS quality assurance. • Interpretation and application of detailed annotation guidelines. • Language-based tasks like transcription, captioning, and prompt-response writing • Have 1+ years of hands-on experience in Autonomous Vehicle, ADAS, or closely related data annotation work. • Demonstrate a strong understanding of annotation quality standards and guidelines. • Have excellent attention to detail and the ability to work accurately on repetitive and complex tasks. • Be able to meet defined productivity and quality expectations. • Be available for potential project deployment after successfully completing the assessment process. • Be willing to complete experience verification and a practical skills assessment. • Reading and writing proficiency in English • The Training will be a 2-week, 80-hour in-person boot camp combining theory, practical exercises, and daily skill checks. • AV fundamentals: Scene understanding, object classification, LiDAR/point clouds, 3D annotation, precision, and 2D/3D correlation. • Driving and temporal reasoning: Tracking over time, ego behaviour, traffic and road context, agent interaction, and spatio-temporal reasoning. • Advanced reasoning: Logical linking, causal/VLA reasoning, and working with evidence and uncertainty. • Quality and adaptability: Attention to detail, learning agility, adapting to changing guidelines, and independent QA. • Hands-on application: Learners apply concepts through practical annotation tasks, calibration, feedback, and exercises, not classroom learning alone. • Post-Training assessment: Five evaluation tasks combining tool-based scoring and expert review, with critical gates for technical execution, reasoning, quality, and adaptability. • Production readiness: Trainees who meet the required standard move into production as project opportunities become available

Listed on MyJobMag — applications are handled there, not on NairobiCity.

0 Commentarii 0 Distribuiri
Nairobi City https://nairobicity.co.ke