Key Skills

Software

CVAT

Labelbox

Label Studio

Roboflow

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Image

Video

Top Task Types

Bounding Box

Entity Ner Classification

Object Detection

Point Key Point

Polygon

Freelancer Overview

I am a versatile AI Data Annotator with extensive hands-on experience in creating high-quality datasets for computer vision and NLP models, sourced from freelance clients on Twitter and Reddit. Specializing in diverse projects like architecture classification, autonomous vehicles, highway security monitoring (annotated over 2,300 images), inventory tracking, pose tracking, emotion/sentiment analysis, and LLM evaluation, I've handled video, satellite imagery, still images, and text annotation using tools such as LabelStudio, CVAT, and Roboflow. My technical skills include working with YOLO v8 and v11 on COCO datasets, training custom YOLO models, and developing Android applications for real-time model testing on mobile devices. Committed to precision and efficiency, I deliver annotations that enhance AI performance in real-world applications like security, autonomous systems, and beyond.

Labeling Experience

Interior Design Data Labeler

Label StudioImage

Annotated 1,200+ kitchen decor images using Label Studio for object detection in interior design AI models. Classes included: "Island", "Upper cabinet", "Worktop", "drawer", "handle", "light", "lower cabinet", "Stove". Ensured high-quality bounding box and polygon labels for precise element identification, contributing to improved AI-driven design recommendations. Project budget: $200–$400; Duration: 1–7 days; Industries: (Furniture), Real Estate, AI for Design Tools (+5 related).

Annotated 1,200+ kitchen decor images using Label Studio for object detection in interior design AI models. Classes included: "Island", "Upper cabinet", "Worktop", "drawer", "handle", "light", "lower cabinet", "Stove". Ensured high-quality bounding box and polygon labels for precise element identification, contributing to improved AI-driven design recommendations. Project budget: $200–$400; Duration: 1–7 days; Industries: (Furniture), Real Estate, AI for Design Tools (+5 related).

2025 - 2025

Video Annotation Specialist (UFC Fight Footage Project)

CVATVideoBounding Box

Successfully completed a high-precision video annotation project for UFC fight footage using Label Studio. Involved frame-by-frame and sequence labeling of fighters and referees across thousands of video clips to train AI models for action recognition, fighter tracking, and highlight generation. Total classes labeled: 20 (Fighters & referees meticulously annotated, including Conor McGregor, Jon Jones, Khabib Nurmagomedov, Islam Makhachev and 15 others, and Referee as a combined class). Each fighter and referee assigned unique bounding boxes and tracked across sequences, ensuring consistent IDs even during fast movement, clinches, and ground positions. Project budget: $1,500–$2,000; Duration: 7–14 days; Industries: Sports Analytics, Computer Vision.

Successfully completed a high-precision video annotation project for UFC fight footage using Label Studio. Involved frame-by-frame and sequence labeling of fighters and referees across thousands of video clips to train AI models for action recognition, fighter tracking, and highlight generation. Total classes labeled: 20 (Fighters & referees meticulously annotated, including Conor McGregor, Jon Jones, Khabib Nurmagomedov, Islam Makhachev and 15 others, and Referee as a combined class). Each fighter and referee assigned unique bounding boxes and tracked across sequences, ensuring consistent IDs even during fast movement, clinches, and ground positions. Project budget: $1,500–$2,000; Duration: 7–14 days; Industries: Sports Analytics, Computer Vision.

2025 - 2025

Image Segmentation Specialist

CVATImageBounding BoxPolygon

Labeled and validated image data for autonomous computer vision applications using CVAT, reducing ghost object false positives and improving incident response time by 25%. Performed polygon and bounding box segmentation on high resolution images (e.g., 24MP+), achieving 0.96 mean IoU in internal validations.

Labeled and validated image data for autonomous computer vision applications using CVAT, reducing ghost object false positives and improving incident response time by 25%. Performed polygon and bounding box segmentation on high resolution images (e.g., 24MP+), achieving 0.96 mean IoU in internal validations.

2025 - 2025

Autonomous Vehicle Dataset Annotator - Highway Security and Monitoring ProjectAutonomous Vehicle Dataset Annotator - Highway Security and Monitoring Project

RoboflowImageBounding BoxPolygon

Annotated over 2,300 images and videos for an autonomous vehicle's dataset for person, vehicle type, obstruction detection in a highway security and monitoring project sourced from Twitter and Reddit clients, using Label Studio. Performed bounding boxes for object detection and classification, integrating with YOLO v11 on COCO format; trained the yolo model and developed Android app for real-time testing. Maintained 95%+ accuracy through iterative reviews, guideline adherence, and validation against ground truth data to ensure reliable AI performance in dynamic environments.Labeled and validated image data for autonomous computer vision applications using CVAT, reducing ghost object false positives and improving incident response time by 25%. Performed polygon and bounding box segmentation on high resolution images (e.g., 24MP+), achieving 0.96 mean IoU in internal validations.

Annotated over 2,300 images and videos for an autonomous vehicle's dataset for person, vehicle type, obstruction detection in a highway security and monitoring project sourced from Twitter and Reddit clients, using Label Studio. Performed bounding boxes for object detection and classification, integrating with YOLO v11 on COCO format; trained the yolo model and developed Android app for real-time testing. Maintained 95%+ accuracy through iterative reviews, guideline adherence, and validation against ground truth data to ensure reliable AI performance in dynamic environments.Labeled and validated image data for autonomous computer vision applications using CVAT, reducing ghost object false positives and improving incident response time by 25%. Performed polygon and bounding box segmentation on high resolution images (e.g., 24MP+), achieving 0.96 mean IoU in internal validations.

2025 - 2025

Data Labelling Specialist

Label StudioTextQuestion AnsweringDiagnosis

Labeled and validated medical text data for NLP models using Label Studio, resulting in a 20% improvement in dataset quality. Conducted usability testing on annotated health content to inform AI training decisions. Worked closely with domain experts to translate complex health queries into structured annotations.

Labeled and validated medical text data for NLP models using Label Studio, resulting in a 20% improvement in dataset quality. Conducted usability testing on annotated health content to inform AI training decisions. Worked closely with domain experts to translate complex health queries into structured annotations.

2023 - 2025

Show more

Education

Work History