Curriculum Vitae

Professional Summary

Full-Stack Web Developer and AI Training & Evaluation Professional based in Nigeria. I build modern, responsive websites and web applications for businesses, and contribute to AI training and evaluation workflows that improve the quality, accuracy, and usefulness of AI-generated outputs.

Technical Skills

Frontend

React.js · JavaScript · TypeScript · Vite · Tailwind CSS · Responsive Web Design

Backend & Development

Backend Development · Python · API Integration · Web Application Development · GitHub · Supabase · Vercel

AI Training & Evaluation

AI Model Training · LLM Response Evaluation · AI Output Quality Assessment · Instruction Following Evaluation · Text-to-Image Evaluation · Reference-to-Image Evaluation · Visual Quality Assessment · AI Alignment and Responsible AI Review

Selected Development Projects

• FLYBIZ — Logistics & Travel

  flybiz.ng

  A business website for a logistics and travel company, designed to present its services and provide customers with an accessible online presence.

• BENELITE GIFTED SCHOOLS — Education

  benelitegiftefschools.com.ng

  An educational institution website designed to communicate school information and provide a professional digital presence.

• MJN TRAVEL CONSULT — Travel Consultancy

  mjntravelconsult.site

  A website developed for a travel consultancy business to showcase its services and establish an online presence.

AI Training & Evaluation Experience

Platform-based project work — Outlier, Handshake

• AI response evaluation: Reviewing language model responses for accuracy, helpfulness, tone, and completeness.
• Model output quality assessment: Rating outputs against structured rubrics and explaining the reasoning behind each judgement.
• Instruction-following assessment: Checking whether a response actually does what the prompt asked — including constraints and format.
• Text-to-image output evaluation: Assessing how faithfully generated images reflect the written prompt.
• Reference-image consistency: Comparing generated images against reference inputs for identity, style, and detail consistency.
• Visual quality & alignment: Flagging artefacts, composition issues, and outputs that conflict with responsible AI guidelines.