Kennedy Munyasya

Key Skills

Software

Appen

CVAT

Dataloop

Scale AI

SuperAnnotate

Labelbox

Roboflow

Top Subject Matter

No subject matter listed

Top Data Types

No data types listed

Top Task Types

Bounding Box

Object Detection

Point Key Point

Polyline

Segmentation

Freelancer Overview

I am a dedicated Data Labeller and AI Training Specialist with hands-on experience in labeling and organizing data for machine learning and artificial intelligence projects. My work involves accurately tagging text, image, and audio datasets to help train high-performing AI systems. I’m skilled in using annotation tools such as Label Studio, Labelbox, and Amazon SageMaker Ground Truth, ensuring every task meets strict quality and consistency standards. I have contributed to projects in Natural Language Processing (NLP), Computer Vision, and Speech Recognition, providing data that improves chatbot communication, image detection, and voice recognition models. My strong attention to detail, understanding of linguistic context, and translation ability (English–Swahili) make me well-suited for diverse AI tasks. I take pride in producing accurate, clean, and well-structured data that helps AI systems learn and perform better across different industries.

Labeling Experience

Video Object Detection and Action Recognition Project

CVATVideoBounding BoxPoint Key Point

Annotated and tracked objects across video frames to train computer vision models for action recognition and object detection. Tasks included drawing bounding boxes around moving objects, labeling actions, and segmenting relevant areas in each frame. Ensured high-quality annotations by following strict guidelines and performing quality reviews. The project involved analyzing hundreds of hours of video footage, helping improve model accuracy for motion detection and scene understanding.

Annotated and tracked objects across video frames to train computer vision models for action recognition and object detection. Tasks included drawing bounding boxes around moving objects, labeling actions, and segmenting relevant areas in each frame. Ensured high-quality annotations by following strict guidelines and performing quality reviews. The project involved analyzing hundreds of hours of video footage, helping improve model accuracy for motion detection and scene understanding.

2020

Data Labeling for AI Training

LabelboxAudioBounding BoxPoint Key Point

Provided high-quality annotation and labeling for diverse datasets to train AI and machine learning models. Tasks included tagging text for NLP, creating bounding boxes and segmentation for images and videos, annotating key points in 3D/sensor data, and transcribing audio for speech recognition. Maintained strict quality standards and accuracy to ensure AI systems learn efficiently and perform reliably across real-world scenarios.

Provided high-quality annotation and labeling for diverse datasets to train AI and machine learning models. Tasks included tagging text for NLP, creating bounding boxes and segmentation for images and videos, annotating key points in 3D/sensor data, and transcribing audio for speech recognition. Maintained strict quality standards and accuracy to ensure AI systems learn efficiently and perform reliably across real-world scenarios.

2023 - 2025

3D Sensor Data Annotation for Human Motion Analysis

Scale AI3D SensorPoint Key PointCuboid

Worked on labeling 3D sensor and LiDAR data to track human movements and interactions for AI-powered robotics and motion analysis systems. Tasks included marking key points on human figures, drawing cuboids around detected objects, and annotating specific actions to help AI models understand spatial relationships and movement patterns. Ensured accuracy and consistency across frames to maintain high-quality datasets for model training. This project involved analyzing large-scale 3D datasets and contributed to improving AI perception in real-world environments.

Worked on labeling 3D sensor and LiDAR data to track human movements and interactions for AI-powered robotics and motion analysis systems. Tasks included marking key points on human figures, drawing cuboids around detected objects, and annotating specific actions to help AI models understand spatial relationships and movement patterns. Ensured accuracy and consistency across frames to maintain high-quality datasets for model training. This project involved analyzing large-scale 3D datasets and contributed to improving AI perception in real-world environments.

2022 - 2024

Medical Imaging Annotation for AI Diagnostics

RoboflowImageBounding BoxSegmentation

I led a high-impact data labeling project focused on annotating medical imaging datasets (X-rays, CT scans, and MRIs) to support the development of AI diagnostic tools. The goal was to train models to detect conditions such as pneumonia, tumors, and bone fractures with high precision.

I led a high-impact data labeling project focused on annotating medical imaging datasets (X-rays, CT scans, and MRIs) to support the development of AI diagnostic tools. The goal was to train models to detect conditions such as pneumonia, tumors, and bone fractures with high precision.

2021 - 2024

Education

Work History