Virgil Darias
Poblacion, Sta. Catalina Negros Oriental
Summary
Results-driven Data Labeler with Scale AI, achieving 98.7% accuracy on 2M+ images. Expert in image annotation techniques, including bounding boxes and segmentation. Enhanced team performance through quality audits and feedback, demonstrating strong analytical skills and attention to detail. Proven ability to contribute to complex projects like LiDAR point cloud annotation.
Overview
4
4
years of professional experience
Work History
Data Labeler
Scale AI (Remote)
03.2022 - Current
- Achieved 98.7% average accuracy across 2M+ annotated images
- Created and maintained project-specific labeling guidelines, reducing ambiguity errors by 45%
- Performed quality audits and provided feedback loops that
- improved team accuracy from 94% to 99.2%
- Contributed to LiDAR point cloud annotation and sensor fusion projects
- Annotated 500K+ images and videos for object detection, facial landmark, and pose estimation tasks
Education
High School Diploma -
Sta. Catalina National Highschool
Sta. Catalina Negros OrientalSkills
- Image: Bounding boxes, polygons, semantic/instance segmentation, keypoints, panoptic segmentation
- Video: Object tracking, action recognition, temporal segmentation
Annotation Types
- Text: NER, sentiment, relation extraction, summarization, translation quality
- 3D: LiDAR point clouds, 3D cuboids, depth estimation
- Audio: Transcription, speaker diarization, emotion labeling
Additional Information
- Available for full-time, contract, or freelance opportunities
- Flexible with global time zones (previously worked with teams in US, Europe, and Asia)
- Strong attention to detail with proven ability to maintain consistency on long-running projects
Tools
Scale AI, Labelbox, CVAT, SuperAnnotate, Dataloop, Appen, Encord, V7 Labs, Prodigy
Languages
English
Advanced (C1)
Timeline
Data Labeler
Scale AI (Remote)
03.2022 - Current
High School Diploma -
Sta. Catalina National Highschool