AI & Machine Learning Engineer
Building production AI systems that remember, recommend, and moderate at scale.
I design and ship applied AI products across RAG, GraphRAG, recommender systems, content moderation, computer vision, and scalable ML infrastructure.
Proof of scale
Systems shipped where reliability, latency, and trust matter.
Selected systems
Applied AI work shaped as products, not demos.
Each system connects modeling choices to product outcomes: retrieval quality, schema validity, safety throughput, ranking performance, and stakeholder trust.
Persistent GraphRAG meeting intelligence
Built a meeting-memory layer that turns transcripts from sales, HR, onboarding, support, and 1:1s into grounded Q&A, action items, follow-ups, and evolving contact memory.
- LangGraph multi-agent orchestration
- Pinecone and ChromaDB retrieval backends
- Evaluation across faithfulness, latency, WER, and schema validity
Creator recommendation and ranking engine
Architected a hybrid recommendation system combining matrix factorization, graph neural networks, content signals, vector search, and LightGBM ranking.
- 1.4M+ user nodes and 10M+ relationships
- Neo4j graph mapping with Qdrant embeddings
- 120% growth in follow engagement
High-throughput moderation pipelines
Scaled ML moderation for video, comments, and profile images with transformer models, confidence calibration, asynchronous queues, and cloud deployment.
- 25K+ videos and 70K+ comments processed daily
- ViT classifiers with Logistic Regression and SVM thresholds
- Google Vertex AI, Pub/Sub, AWS EKS, and SQS
Experience
A track record across AI infrastructure, ML products, and data-heavy workflows.
From early data science work to production-grade AI platforms, the throughline is turning messy operational problems into reliable ML systems.
03/2026 - Present
AI Engineer, AideMeet
Built GraphRAG-powered meeting intelligence with persistent memory, retrieval, multi-agent workflows, benchmarking, and local model serving exploration.
12/2025 - 03/2026
Machine Learning Engineer, Pingtop
Shipped creator recommendations, video moderation, comment moderation, and profile-image safety systems using graph databases, vector search, cloud queues, Kubernetes, and transformer models.
08/2024 - 03/2025
Machine Learning Engineer, RightClick IT Solutions
Developed an enterprise RAG system over 22,000+ technical files with OCR, robust parsing, embeddings, Chroma DB, FastAPI, Celery, Redis, Docker, and AWS EC2.
07/2022 - 07/2024
Applied Machine Learning Scientist, Edvantage Learning Solutions
Consulted enterprise clients, prototyped fault detection and physics-informed ML, built Streamlit proof-of-concepts, and trained 200+ engineering professionals.
02/2022 - 07/2022
Data Scientist, Heritage Energy Operational Services
Built predictive analytics, automated Power BI dashboards, and ML workflows for operational asset selection and production KPI monitoring.
Technical range
The stack behind the systems.
Strength across applied modeling, retrieval, cloud deployment, data engineering, and product-facing AI evaluation.
AI systems
RAG, GraphRAG, LangChain, LangGraph, LLM evaluation, prompt workflows, local model serving
Machine learning
PyTorch, Transformers, Vision Transformers, LightGBM, GNNs, Matrix Factorization, SVMs
Data and Databases
PostgreSQL, MongoDB, Neo4j, ChromaDB, Pinecone, Qdrant, ETL/ELT, OCR pipelines
Backend and MLOps
Python, FastAPI, Docker, Kubernetes, Celery, Redis, AWS EC2, AWS EKS, Google Vertex AI
Credentials
Education and certifications that support the engineering practice.
M.Sc. Artificial Intelligence (in view).
Woolf University, online, Malta
B.Eng. Petroleum Engineering
University of Port Harcourt, Port Harcourt, Nigeria
Data Engineer Certification
DataCamp
AI Lab: Deep Learning for Computer Vision
WorldQuant University
Book a meeting
Schedule a focused conversation in Lagos time.
Select a slot for AI engineering, ML systems, RAG, recommendation, or consulting conversations. The request opens as an email with the meeting details ready to send.
Contact
Let us build something reliable, useful, and ready for real users.
I am open to AI engineering, machine learning engineering, and applied AI product roles where production quality matters as much as model quality.