Lead AI/ML & LLM Engineer
Luminor Terminal LTD (Revluma)
Abuja, Nigeria · Remote
– Present
David Temitayo Okanlawon
AI/ML Engineer & Data Scientist
About me
I design and build end-to-end AI and machine learning systems, covering everything from problem definition and data preparation to model development, deployment, and continuous improvement. My work brings together data science, software engineering, and modern AI methods to create reliable, scalable solutions.
I have applied this expertise across diverse sectors, including technology and finance, turning complex data into practical products and better decisions.
Technical skills
Machine learning
Scikit-learn, PyTorch, TensorFlow/Keras, natural language processing, computer vision, feature engineering, and large language models.
Data
Python, SQL, PostgreSQL, data analysis, data visualisation, web scraping, data ingestion pipelines, Spark, and Hadoop.
Engineering
MLflow, Docker, CI/CD, Git, GitHub, Redis, microservices, asynchronous architectures, and autonomous agents.
Platforms
AWS, GCP, Azure, Streamlit, Jupyter, and Google Colab.
Professional experience
IT & Software Intern
Federal Mortgage Bank of Nigeria
Abuja, Nigeria
–
Network & Infrastructure Intern
Chipset Technologies Limited
Abuja, Nigeria
–
Data Scientist Trainee
SQI College of ICT
Ogbomoso, Nigeria
–
Featured projects
Gender Identifier
A computer vision application built with Streamlit, FairFace, RetinaFace, eDifFIQA, and ONNX Runtime. It analyses uploaded images and permission-controlled webcam captures, validates face visibility and image quality, and returns a binary facial-presentation estimate when one usable face is detected.
ToxiScan
A contextual NLP moderation tool built with PyTorch, Transformers, and Streamlit. It identifies potentially toxic, hateful, threatening, and abusive language in pasted text, a wide range of uploaded documents, public webpages, and accessible comments.
Card Identifier
A computer vision application powered by a ResNet18 model and optimised with ONNX Runtime. It identifies the suit and rank of a playing card while validating image quality and rejecting unclear or ambiguous inputs.
Core Banking Engine
A Streamlit and SQLite banking demonstration featuring atomic transaction processing, double-entry accounting, database-level journal validation, idempotency safeguards, customer ledgers, and administrative reconciliation.
Python Tutorial Chatbot
A lightweight learning assistant built with Python and Streamlit. It retrieves grounded explanations, runnable examples, related topics, and official documentation links across 40 Python tutorial topics using typo-tolerant, synonym-aware, and symbol-aware query matching.