Freelancer

Key Skills

Software

Remotasks

Top Subject Matter

Autonomous Vehicles (3D LiDAR perception, object detection, tracking)

Computer Vision (image and video annotation, visual recognition datasets)

AI Training Data Quality Assurance (dataset review, validation, and error detection)

Top Data Types

3D Sensor

Image

Video

Top Task Types

Bounding Box

Segmentation

Cuboid

Polygon

Evaluation/Rating

Entity (NER) Classification

Freelancer Overview

Senior Annotation Quality Analyst with 6 years of experience in AI data labeling and quality assurance, specializing in 3D LiDAR, video, and 2D image annotation. Experienced in reviewing and validating large-scale datasets used for computer vision and autonomous systems, ensuring high accuracy in bounding box and cuboid placements, object classification, and tracking consistency across frames. Skilled in identifying annotation errors, enforcing guideline compliance, and maintaining dataset quality standards for machine learning model training. Progressed through structured roles from Trainee (L0) to Trainee Reviewer (L1), Senior Reviewer (L10), and Modular L10 Contributor, allowing cross-project deployment based on operational needs. Recognized for strong attention to detail and consistency in data validation, as well as providing corrective feedback to improve annotator performance and overall dataset reliability in production-level AI pipelines.

Labeling Experience

Senior Annotation Quality Analyst (3D LiDAR Specialist)

3D SensorBounding Box

Worked on AI data annotation and quality assurance for autonomous vehicle and computer vision systems, specializing in 3D LiDAR sensor data. Responsible for reviewing and validating bounding box and cuboid annotations to ensure accurate object detection, classification, and spatial positioning within point cloud environments. Performed quality checks on image, video, and LiDAR datasets, identifying labeling errors, inconsistencies, and tracking issues. Ensured datasets met strict annotation guidelines for machine learning model training and contributed to improving overall data quality through structured feedback and review processes.

2019 - Present

Education

Work History