George Gategi

Key Skills

Software

CVAT

Dataloop

Hasty

Labelbox

Label Studio

SuperAnnotate

Other

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Action Recognition

Bounding Box

Point/Key Point

Polygon

Segmentation

Freelancer Overview

I am an experienced Data Labeling and AI Training Specialist with over three years of hands-on expertise in developing high-quality datasets for computer vision, NLP, and speech recognition models. My background includes extensive work in image, video, text, audio, and LiDAR annotation, contributing to global projects that power advanced AI systems. I have worked with annotation tools such as Labelbox, CVAT, SuperAnnotate, Dataloop, and AWS SageMaker Ground Truth, ensuring accuracy, consistency, and adherence to client guidelines. My proven ability to manage large-scale labeling tasks, perform detailed quality checks, and train new annotators sets me apart. I bring strong analytical skills, ISO-standard quality awareness, and a deep understanding of machine learning data pipelines — making me a reliable partner in producing gold-standard AI training data. My background in Economics and Sociology strengthens my analytical and contextual understanding, while my work with organizations like Smartone.ai, CloudFactory, and Adept Technologies Ltd has refined my attention to detail, quality assurance, and data security practices. I take pride in delivering precise annotations that enhance machine learning model accuracy and ensure ethical AI development.

Labeling Experience

Data Labelling

SuperannotateVideoText GenerationEmotion Recognition

I made an extensive contribution to the video-to-text labelling project (luma writers), successfully delivering over 4,000 high-quality tasks with an average QC of 4.2. This experience enhanced my precision, consistency, and ability to work under structured guidelines. My performance has been recognized, and for reference, who can attest to my reliability and work ethic.

I made an extensive contribution to the video-to-text labelling project (luma writers), successfully delivering over 4,000 high-quality tasks with an average QC of 4.2. This experience enhanced my precision, consistency, and ability to work under structured guidelines. My performance has been recognized, and for reference, who can attest to my reliability and work ethic.

2025 - 2025

Education

Work History