Toyyibah B.

Key Skills

Software

Appen

Top Subject Matter

AI Automation & System Integration — Designing and deploying end-to-end automation workflows using n8n, Twilio, Supabase, and Flask across multiple client and academic projects

AI Model Development & Training — Building and training ML models (XGBoost), integrating AI APIs (OpenAI GPT-4.1-mini), prompt engineering for real-world applications (NeuroPath, HexaScope)

Full-Stack AI Application Development — Building complete AI-powered web applications from backend to frontend, combining Python, Flask, Supabase, and React/Lovable into production-ready systems

Top Data Types

Video

Image

Top Task Types

Action Recognition

Function Calling

Freelancer Overview

I am a final-year Computer Science student with hands-on experience in AI data annotation and training data preparation, having worked with Atlas Capture to label and annotate video datasets used to train AI models for robotics and computer vision. I bring strong attention to detail, consistency, and a solid understanding of data quality standards essential for producing accurate training data at scale. Beyond annotation, I have built and deployed multiple AI-powered systems from scratch — including NeuroPath, an XGBoost-based stroke rehabilitation scheduling system, and HexaScope, an insect classification app powered by the OpenAI GPT-4.1-mini vision API. My hands-on experience training machine learning models, engineering prompts, and integrating AI APIs gives me a deeper understanding of what high-quality labeled data actually needs to look like on the other side — making me a more precise and purposeful annotator than someone without that technical background.

Labeling Experience

Independent Consultant — Freelance AI Automation & Web Development

Function Calling

Built AI automation workflows and systems that connect data inputs to model or application steps. Implemented chatbots, lead pipelines, and booking systems using workflow orchestration and API integrations. While not explicitly described as dataset labeling, the work involved structured data routing and generation of interaction data used in AI-enabled products. • Designed WhatsApp chatbot automation flows • Built lead pipelines and booking workflows • Integrated tools such as Twilio and Google Forms • Used Supabase for storing and managing workflow data

2025 - Present

AI Data Annotator — Atlas Capture (Remote)

VideoAction Recognition

Labeled video datasets to support AI model training for robotics and computer vision. Performed action, object, and event classification across video frames while ensuring annotation quality. Maintained accuracy and consistency across large volumes to meet training standards. • Classified actions across sequential video frames • Labeled objects and events visible in the footage • Applied quality assurance checks for consistency • Ensured annotations met AI training data requirements

2026

Education

Work History