Elgen Eñigo

Key Skills

Software

CVAT

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Image

Video

Top Label Types

Classification

Cuboid

Polygon

Polyline

Segmentation

Freelancer Overview

I am an accuracy-driven data professional with hands-on experience in data validation, structured record consolidation, and high-precision annotation for AI training datasets. My background includes validating and updating large, multi-tab trackers in Excel and Google Sheets, managing documentation workflows, and ensuring completeness and consistency in reporting. I have completed over 140 annotation tasks on 3D LiDAR point cloud and 2D video projects, maintaining a 93–95% QA agreement rate by strictly following evolving guidelines and handling complex edge cases. I am proficient in using platform-based labeling tools and thrive in roles that demand disciplined documentation control, high attention to detail, and reliable remote work readiness. My goal is to support high-quality data labeling and verification projects that require both accuracy and efficiency.

Labeling Experience

3D LiDAR + 2D Segmentation Annotator | Reviewer Track (Scale AI via Remotasks)

Scale AI3D SensorPolylineSegmentation

Freelance data annotator on Remotasks (Scale AI workflow) for road-scene perception datasets using 3D LiDAR point clouds and 2D images. Completed 140 production tasks (116 LiDAR annotation/segmentation + 24 2D image segmentation) plus 4 prelabeling experiment tasks across 10 projects. Produced 3D cuboids/boxes, lane-line polylines, and segmentation masks; labeled vehicles and pedestrians (actions/movement), traffic signs, and traffic light state/color indicators. Maintained 93%–95% QA agreement and performed reviewer-track checks as a Super Reviewer Trainee (guideline enforcement, edge-case escalation).

Freelance data annotator on Remotasks (Scale AI workflow) for road-scene perception datasets using 3D LiDAR point clouds and 2D images. Completed 140 production tasks (116 LiDAR annotation/segmentation + 24 2D image segmentation) plus 4 prelabeling experiment tasks across 10 projects. Produced 3D cuboids/boxes, lane-line polylines, and segmentation masks; labeled vehicles and pedestrians (actions/movement), traffic signs, and traffic light state/color indicators. Maintained 93%–95% QA agreement and performed reviewer-track checks as a Super Reviewer Trainee (guideline enforcement, edge-case escalation).

2019 - 2020

Education

Work History