Mubaraka Gbadamosi

Key Skills

Software

Toloka

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Top Label Types

Point Key Point

Action Recognition

Data Collection

Freelancer Overview

I am an experienced AI data contributor and tester with a strong background in data labeling, annotation, and dataset validation for machine learning and computer vision projects. I have worked on high-precision data collection and annotation tasks with platforms like uTest (Applause), Atlas Capture, Crowdgen, and Toloka, consistently maintaining a 95%+ acceptance rate through strict adherence to quality guidelines. My experience includes generating and validating image and video datasets for object detection, facial recognition, and behavioral pattern analysis. I am skilled in using tools such as Google Workspace, Microsoft Excel, and various QA platforms, and have contributed to projects in fintech, e-commerce, and media domains. My attention to detail, technical proficiency, and commitment to data quality ensure that I deliver reliable and accurate training data for AI and machine learning models.

Labeling Experience

Face Dataset Collection for Facial Recognition & Liveness Detection

TolokaImagePoint Key PointAction Recognition

I contributed to a large scale Biometric Data Collection project focused on enhancing Computer Vision models. My role involved producing and uploading longitudinal facial data, comparing historical images with current captures to assist in the training of facial Aging algorithms. To improve Pose Estimation accuracy. I captured and labeled specific facial orientation(yaw and pitch), including upward, downward, and lateral views. Additionally, i participated in Liveness Verification tasks designed to trains systems in distinguishing between live subjects and static spoofing attempts. Throughout the projects, i maintained strict Quality Control, ensuring all datasets met rigorous technical requirements for lighting, framing, and resolution as defined by the projects metadata standards.

I contributed to a large scale Biometric Data Collection project focused on enhancing Computer Vision models. My role involved producing and uploading longitudinal facial data, comparing historical images with current captures to assist in the training of facial Aging algorithms. To improve Pose Estimation accuracy. I captured and labeled specific facial orientation(yaw and pitch), including upward, downward, and lateral views. Additionally, i participated in Liveness Verification tasks designed to trains systems in distinguishing between live subjects and static spoofing attempts. Throughout the projects, i maintained strict Quality Control, ensuring all datasets met rigorous technical requirements for lighting, framing, and resolution as defined by the projects metadata standards.

2025 - 2025

Education

Work History