I’m an energy & petroleum engineer turned AI-practitioner and educator who builds production-ready ML systems, teaches engineering & data science, and leads product initiatives at the intersection of Energy × AI × EdTech.
- 🎓 M.Sc & B.Sc in Petroleum Engineering — specialising in reservoir simulation, production forecasting & offshore operations
- 🎓 MBA coursework, preparing for a PhD focused on physics-informed ML (PINNs) for energy systems
- 💼 Built and scaled educational AI platforms (20K+ users) and knowledge-graph Q&A bots using LangChain + Neo4j
- 🔧 Comfortable across full-stack development: from data pipelines → ML models → cloud deployment → product metrics
- 🌍 Based in Benin City, Nigeria — open to remote / hybrid roles & mentoring globally
| Category | Technologies & Tools |
|---|---|
| Languages | Python · SQL · Julia · JavaScript (Node/Next.js) · C · Fortran · Kotlin · Bash |
| Machine Learning | PyTorch · TensorFlow · scikit-learn · Pandas · NumPy · SciPy |
| NLP & Retrieval | HuggingFace · LangChain · vector DBs · dense + sparse retrieval · RLHF |
| Knowledge Graphs | Neo4j · custom embedding pipelines · semantic search |
| Cloud & DevOps | GCP (Vertex AI, Cloud Functions) · Azure · Docker · Kubernetes · CI/CD (GitHub Actions) · MLflow/DVC · Terraform |
| Web / API / Product | FastAPI · Flask · Next.js · Node.js · REST / GraphQL · Paystack / PayPal integrations |
| Energy Engineering | Petrel · CMG · SolidWorks/Inventor · Power BI · Excel modelling · UML / Gantt / CPM |
| Management & Biz | Road-maps · OKRs/KPIs · Capital-budgeting (NPV/IRR) · Agile/Scrum · Team mentoring & hiring |
- Agentic EdTech Platform (22K+ users) — Lead product engineer for an AI-powered educational platform: built automated grading pipelines using LangChain/HuggingFace, deployed on GCP, integrated billing & analytics.
- University AI Grading System — Designed and deployed an exam-assessment stack using ML models + serverless functions; onboarded ~6K students in month 1.
- Knowledge-Graph Q&A Bot — Ingested Wikipedia + domain data into Neo4j, built retrieval & answer pipeline with LangChain, enabled interactive query & answer system.
- Wellhead/Tubing-Head Pressure Forecasting — Applied RandomForest regression and feature-engineering for production forecasting in the oil & gas domain.
- End-to-End Product & Infra Work — Built payment flows (Paystack/PayPal) on Wix, architected GCP storage + media pipelines, set up CI/CD for multiple repos.
- R&D & Prototyping — Researching PINNs & digital-twins for fluid-flow modelling, tensor methods and Laplace-Beltrami geometry in reservoirs.
- Understand the constraints — physics, data-quality, business KPIs
- Rapid prototype — minimum viable pipeline & validation
- Productionise — containerise, deploy, monitor, iterate
- User-centric iteration — feedback loops, metrics, experiment
This blend of domain-engineering + ML + product mindset gives me an edge in solving “real problem” systems.
I’m open to:
- Product / Technical Lead roles in AI-first EdTech or Energy tech
- Contract engagements: ML pipelines, knowledge-graph systems, forecasting
- Mentoring: Python, numerical & engineering computing, ML productisation
- Speaking & workshops: Python classes (2nd-year uni), curriculum design
📫 Feel free to reach out: enosmath@gmail.com
- I’ve organised youth STEM workshops and coordinated volunteer academic-author teams.
- I once used GitHub to launch a remote-first training programme for a Green Tech startup.
- When I’m not coding: I’m thinking about reservoir dynamics, reading science-fiction, or designing curricula.
“Build systems that learn, adapt, and empower — whether to forecast oil-well behaviour or students’ learning curves.”
Thanks for visiting my profile 🙏
Let’s build something meaningful together!