Mercy Mogambi

Key Skills

Software

Appen

CloudFactory

CVAT

Hasty

OneForma

Roboflow

Top Subject Matter

No subject matter listed

Top Data Types

Geospatial Tiled Imagery

Image

Video

Top Task Types

Bounding Box

Classification

Mapping

Polygon

Segmentation

Freelancer Overview

I am a detail-oriented Data and AI Specialist with hands-on experience in data labeling and AI training workflows, particularly in image and video annotation. I have worked on high-volume annotation projects involving object detection, segmentation, pixel classification, and bounding box labeling to produce high-quality datasets for machine learning models. I consistently follow task-specific guidelines and perform quality reviews to ensure accuracy, consistency, and data integrity across large datasets. In addition to annotation, I have a strong understanding of how labeled data supports AI model training and evaluation. I am comfortable using web-based annotation tools, adapting quickly to new platforms, and collaborating with QA teams to improve annotation quality. My attention to detail, reliability in meeting deadlines, and commitment to producing clean, well-structured training data set me apart as a contributor who delivers dependable results for AI-driven projects.

Labeling Experience

Video Annotation for Object Detection & Visual Analysis

HastyVideoBounding BoxClassification

projects involving frame-by-frame labeling of objects and visual elements for AI training. Tasks included drawing bounding boxes, tracking objects across frames, and classifying visual content based on predefined categories. Ensured temporal consistency across frames and followed strict annotation rules to support accurate model learning. Regular collaboration with QA teams helped refine annotation quality and resolve edge cases.

projects involving frame-by-frame labeling of objects and visual elements for AI training. Tasks included drawing bounding boxes, tracking objects across frames, and classifying visual content based on predefined categories. Ensured temporal consistency across frames and followed strict annotation rules to support accurate model learning. Regular collaboration with QA teams helped refine annotation quality and resolve edge cases.

2024 - 2025

Image Annotation & Segmentation for Computer Vision Models

HastyImageBounding BoxPolygon

Annotated large-scale image datasets for computer vision model training. Tasks included drawing precise bounding boxes around objects, performing semantic and instance segmentation, and classifying image elements according to detailed project guidelines. Pixel-level labeling was used to distinguish objects from background and separate multiple instances of the same class. Quality control measures included self-review and QA feedback cycles to ensure high accuracy, consistency, and adherence to annotation standards. The annotated images were used to train and validate AI models for object recognition and scene understanding.

Annotated large-scale image datasets for computer vision model training. Tasks included drawing precise bounding boxes around objects, performing semantic and instance segmentation, and classifying image elements according to detailed project guidelines. Pixel-level labeling was used to distinguish objects from background and separate multiple instances of the same class. Quality control measures included self-review and QA feedback cycles to ensure high accuracy, consistency, and adherence to annotation standards. The annotated images were used to train and validate AI models for object recognition and scene understanding.

2024 - 2025

Education

Work History