Blackn Blank

Key Skills

Software

Labelbox

CVAT

Top Subject Matter

Autonomous vehicles

retail environments

traffic scenes

Top Data Types

Image

Top Task Types

Object Detection

Segmentation

Bounding Box

Freelancer Overview

Senior AI Data Trainer – Computer Vision. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox and CVAT. Education includes Bachelor of Science, N/A (2021) and Certificate, AIDRALabs (2026). AI-training focus includes data types such as Image, Medical, and DICOM and labeling workflows including Object Detection, Segmentation, and Bounding Box.

Labeling Experience

Senior AI Data Trainer – Computer Vision

LabelboxImageObject Detection

As a Senior AI Data Trainer at DataVision Labs, I conducted high-volume annotation and QA of images involving object detection, segmentation, and classification for computer vision projects. My work included refining AI-generated bounding boxes, segmentation masks, and class labels for use in autonomous vehicle and retail AI systems. I led QA cycles, coordinated schema alignment with ML engineers, and participated in the maintenance of large-scale datasets.• Annotated and quality-checked over 320,000 images for object detection, segmentation, and multiclass classification.• Reduced label error rates by 18% through error analysis and correction of AI-generated labels.• Led validation cycles yielding a 97.3% interannotator agreement on production datasets.• Collaborated on annotation schemas improving model accuracy by 6 mAP points.

As a Senior AI Data Trainer at DataVision Labs, I conducted high-volume annotation and QA of images involving object detection, segmentation, and classification for computer vision projects. My work included refining AI-generated bounding boxes, segmentation masks, and class labels for use in autonomous vehicle and retail AI systems. I led QA cycles, coordinated schema alignment with ML engineers, and participated in the maintenance of large-scale datasets.• Annotated and quality-checked over 320,000 images for object detection, segmentation, and multiclass classification.• Reduced label error rates by 18% through error analysis and correction of AI-generated labels.• Led validation cycles yielding a 97.3% interannotator agreement on production datasets.• Collaborated on annotation schemas improving model accuracy by 6 mAP points.

2023 - Present

AI Data Annotation Specialist

LabelboxImageSegmentation

As an AI Data Annotation Specialist at Nexus Annotation Services, I performed polygon segmentation and bounding box annotations for diverse retail product images. I also evaluated pre-labeled datasets for AI vision pilots, addressing systematic labeling gaps and proposing ontology refinements. I maintained high annotation accuracy, supported checklist creation, and trained junior annotators on labeling workflows.• Delivered segmentation and bounding box labels for 40,000+ images across 12 retail product categories.• Achieved a personal annotation accuracy of 98.1% and a 98.5% on-time delivery rate.• Evaluated and documented gaps in zero-shot model outputs, improving annotation ontologies.• Trained new hires on Labelbox and CVAT, standardizing workflow and QA practices.

As an AI Data Annotation Specialist at Nexus Annotation Services, I performed polygon segmentation and bounding box annotations for diverse retail product images. I also evaluated pre-labeled datasets for AI vision pilots, addressing systematic labeling gaps and proposing ontology refinements. I maintained high annotation accuracy, supported checklist creation, and trained junior annotators on labeling workflows.• Delivered segmentation and bounding box labels for 40,000+ images across 12 retail product categories.• Achieved a personal annotation accuracy of 98.1% and a 98.5% on-time delivery rate.• Evaluated and documented gaps in zero-shot model outputs, improving annotation ontologies.• Trained new hires on Labelbox and CVAT, standardizing workflow and QA practices.

2022 - 2023

Junior Image Annotation Analyst

CVATBounding Box

As a Junior Image Annotation Analyst at TechAnnotate Inc., I was responsible for bounding box labeling and image classification on medical images for AI model training. I annotated X-ray and MRI frames with high anatomical precision, ensuring compliance with quality standards. I flagged ambiguous cases for expert review and assisted with dataset curation and documentation.• Labeled over 15,000 X-ray and MRI frames using bounding boxes and classification schemes.• Maintained a QA pass rate of 96.8%, surpassing team averages on regulated datasets.• Supported detection of duplicate images, class imbalance assessment, and label schema documentation.• Collaborated with radiologists to ensure high-quality, reliable training data.

As a Junior Image Annotation Analyst at TechAnnotate Inc., I was responsible for bounding box labeling and image classification on medical images for AI model training. I annotated X-ray and MRI frames with high anatomical precision, ensuring compliance with quality standards. I flagged ambiguous cases for expert review and assisted with dataset curation and documentation.• Labeled over 15,000 X-ray and MRI frames using bounding boxes and classification schemes.• Maintained a QA pass rate of 96.8%, surpassing team averages on regulated datasets.• Supported detection of duplicate images, class imbalance assessment, and label schema documentation.• Collaborated with radiologists to ensure high-quality, reliable training data.

2022 - 2022

Education

Work History