Kennedy

Key Skills

Software

CVAT

Labelbox

Label Studio

SuperAnnotate

Top Subject Matter

Computer Vision

Autonomous Systems

3D Perception

Top Data Types

Image

Video

3D Sensor

Top Task Types

Bounding Box

Segmentation

Polygon

Cuboid

Evaluation/Rating

Object Detection

Freelancer Overview

Computer Vision Data Annotator – Sama, Nairobi Kenya. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include CVAT and Labelbox. Education includes Bachelor of Science, Jomo Kenyatta University of Agriculture and Technology (2023) and Certificate, JKUATES (2023). AI-training focus includes data types such as Image and labeling workflows including Bounding Box and Segmentation.

Labeling Experience

Data Annotation Specialist – Klatch Technologies, Agricultural Crops & Weeds Segmentation Project

LabelboxImageSegmentation

In the Agricultural Crops & Weeds Segmentation Project at Klatch Technologies, I labeled agricultural field images to distinguish crops from weeds for computer vision datasets. The main task was to precisely outline plant boundaries to aid the development of agricultural AI models. Feedback-driven refinement and strict adherence to guidelines were prioritized to ensure accurate annotations. • Segmented various crops and weed plants in agricultural imagery. • Outlined plant contours to reflect natural shapes and patterns. • Incorporated feedback from reviews to enhance accuracy in labeling. • Emphasized consistency and reliability during all annotation tasks.

In the Agricultural Crops & Weeds Segmentation Project at Klatch Technologies, I labeled agricultural field images to distinguish crops from weeds for computer vision datasets. The main task was to precisely outline plant boundaries to aid the development of agricultural AI models. Feedback-driven refinement and strict adherence to guidelines were prioritized to ensure accurate annotations. • Segmented various crops and weed plants in agricultural imagery. • Outlined plant contours to reflect natural shapes and patterns. • Incorporated feedback from reviews to enhance accuracy in labeling. • Emphasized consistency and reliability during all annotation tasks.

2025 - 2025

Data Annotation Specialist – Klatch Technologies, Industrial Metal Segmentation Project

LabelboxImageSegmentation

During the Industrial Metal Segmentation Project at Klatch Technologies, I performed semantic segmentation on images of industrial metal structures. The work focused on creating accurate polygon masks for AI training datasets to meet export-quality standards. This project required adaptation to evolving guidelines to ensure labeling precision and consistency. • Segmented braid-shaped industrial metal images using polygons. • Maintained quality and consistency across multiple dataset versions. • Engaged with reviewers for complex scenario resolution and guideline adherence. • Consistently met or exceeded required annotation standards and accuracy.

During the Industrial Metal Segmentation Project at Klatch Technologies, I performed semantic segmentation on images of industrial metal structures. The work focused on creating accurate polygon masks for AI training datasets to meet export-quality standards. This project required adaptation to evolving guidelines to ensure labeling precision and consistency. • Segmented braid-shaped industrial metal images using polygons. • Maintained quality and consistency across multiple dataset versions. • Engaged with reviewers for complex scenario resolution and guideline adherence. • Consistently met or exceeded required annotation standards and accuracy.

2025 - 2025

Computer Vision Data Annotator – Sama, Nairobi Kenya

CVATImageBounding Box

As a Computer Vision Data Annotator at Sama, I was responsible for annotating objects in images and videos for AI and autonomous systems. I used tools such as CVAT, Labelbox, SuperAnnotate, and V7 to perform high-quality annotations and ensure data quality. The role also gave me exposure to 3D LiDAR processes for autonomous vehicle datasets. • Annotated images and video frames using bounding box and polygon tools. • Collaborated with QA teams to maintain high labeling accuracy and quality standards. • Participated in regular quality checks to ensure consistency and reliability. • Gained introductory experience with 3D sensor and LiDAR dataset annotation.

As a Computer Vision Data Annotator at Sama, I was responsible for annotating objects in images and videos for AI and autonomous systems. I used tools such as CVAT, Labelbox, SuperAnnotate, and V7 to perform high-quality annotations and ensure data quality. The role also gave me exposure to 3D LiDAR processes for autonomous vehicle datasets. • Annotated images and video frames using bounding box and polygon tools. • Collaborated with QA teams to maintain high labeling accuracy and quality standards. • Participated in regular quality checks to ensure consistency and reliability. • Gained introductory experience with 3D sensor and LiDAR dataset annotation.

2024 - 2024

Education

Work History