Judith Mugami

Key Skills

Software

CloudFactory

CVAT

Remotasks

Sama

Telus

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Video

Top Task Types

Bounding Box

Object Detection

Polygon

Polyline

Segmentation

Freelancer Overview

I am a highly experienced Data Labeling Specialist with over six years of expertise in annotating 2D and 3D data for machine learning applications. I have worked extensively on projects involving image and video annotation, object detection, facial recognition, and autonomous vehicle training data. My strong background in quality control and data verification ensures that all labeled datasets meet the highest standards of accuracy and consistency. Throughout my career, I have contributed to leading AI training platforms like SamaSource, Remotask, and CloudFactory, where I consistently met strict deadlines and exceeded quality benchmarks. My strengths include mastering tools for bounding boxes, segmentation, and cuboid annotation, as well as mentoring junior annotators and collaborating effectively in team environments. With a keen eye for detail and a commitment to delivering clean, structured data, I am dedicated to supporting the development of reliable and ethical AI systems.

Labeling Experience

Computer Vision Annotation for Vehicle Detection (CVAT Tool)

CVATImageBounding BoxPolygon

I worked on a large-scale vehicle detection and tracking project using CVAT (Computer Vision Annotation Tool) for a client in the autonomous driving industry. The objective was to accurately label and track vehicles, pedestrians, and other road elements across thousands of video frames to train AI models in object detection and motion prediction.

I worked on a large-scale vehicle detection and tracking project using CVAT (Computer Vision Annotation Tool) for a client in the autonomous driving industry. The objective was to accurately label and track vehicles, pedestrians, and other road elements across thousands of video frames to train AI models in object detection and motion prediction.

2024 - 2024

Autonomous Vehicle Perception – 3D Object Annotation for LIDAR and Camera Data

Scale AIVideoBounding BoxPolygon

Worked on a high-precision data annotation project to train AI models used in self-driving car technology. The focus was on identifying and labeling objects such as pedestrians, vehicles, bicycles, traffic signs, and lane markings from multi-sensor inputs including LIDAR and camera feeds.

Worked on a high-precision data annotation project to train AI models used in self-driving car technology. The focus was on identifying and labeling objects such as pedestrians, vehicles, bicycles, traffic signs, and lane markings from multi-sensor inputs including LIDAR and camera feeds.

2021 - 2023

Education

Work History