Justice Msimuko

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Image

Top Label Types

Bounding Box

Segmentation

Classification

Question Answering

Object Detection

Freelancer Overview

I am a detail-oriented Data Labeling Specialist with hands-on experience in annotating and preparing high-quality training data for AI and machine learning projects. My work as a freelance Data Labeler for Remotasks involved creating precise bounding boxes, performing image segmentation, and classifying objects for computer vision tasks. I excel at maintaining accuracy and consistency in image annotation and object detection labeling, and I am skilled in data collection, validation, and quality assurance. I thrive in remote environments, consistently meeting strict deadlines while ensuring dataset integrity. My strong organizational skills, technical proficiency, and commitment to quality make me a reliable contributor to any AI training data project.

Labeling Experience

Image Annotation & Object Detection

Scale AIImageBounding BoxSegmentation

I worked on multiple computer vision annotation projects on Remotasks focused on object detection and image classification for AI model training. The scope of the projects involved preparing high-quality labelled datasets to support supervised machine learning models. My responsibilities included drawing precise bounding boxes around objects, assigning correct class labels, and following strict annotation guidelines provided for each task. I worked on general object detection datasets involving people, equipment, and everyday scene elements. The project size ranged from hundreds to thousands of images per task batch, and I contributed to labelling over 2,000 images across multiple projects. To ensure quality, I strictly followed annotation standards, maintained consistent box alignment and class accuracy, and reviewed my work before submission. I maintained high accuracy ratings and adhered to quality control.

I worked on multiple computer vision annotation projects on Remotasks focused on object detection and image classification for AI model training. The scope of the projects involved preparing high-quality labelled datasets to support supervised machine learning models. My responsibilities included drawing precise bounding boxes around objects, assigning correct class labels, and following strict annotation guidelines provided for each task. I worked on general object detection datasets involving people, equipment, and everyday scene elements. The project size ranged from hundreds to thousands of images per task batch, and I contributed to labelling over 2,000 images across multiple projects. To ensure quality, I strictly followed annotation standards, maintained consistent box alignment and class accuracy, and reviewed my work before submission. I maintained high accuracy ratings and adhered to quality control.

2021 - 2023

Education

Work History