Building intelligent systems — from production LLM pipelines to published deep learning research. Full-stack developer with a focus on AI/ML solutions that actually ship.
I'm a Data Scientist and Full-Stack Developer based in Nairobi, Kenya, with 3+ years of experience building end-to-end AI systems — from data pipeline to deployment.
Currently completing my MSc in Computer Science at Dedan Kimathi University of Technology, with active research in NLP for low-resource African languages.
I've worked in production environments integrating LLMs at a Swedish tech firm, published in IEEE and arXiv, and taught 700+ university students. I bridge research and real-world engineering.
DeKUT, Nyeri, Kenya
IEEE, arXiv, IST Africa
Production prompt engineering
Low-resource language research
A full-stack skillset with a specialisation in ML/AI systems and LLM engineering.
Proven ability to mentor students, deliver technical presentations, and lead cross-functional teams.
Strong analytical thinking with experience identifying key problems and implementing effective solutions.
Experience working in agile environments and managing stakeholder relationships.
Demonstrated ability to learn new technologies quickly and manage multiple projects simultaneously.
Skilled in planning, organizing, and delivering projects on time using tools like Jira and Trello.
End-to-end solutions spanning healthcare AI, NLP, blockchain, and financial analytics.
CNN-based medical imaging analysis system for lung disease detection, deployed as a web application with real-time inference.
Neural Machine Translation for a low-resource African language pair using custom attention mechanisms. Published at IST Africa 2025.
NLP and ML classifier ensemble detecting postpartum depression signals from patient survey data using Logistic Regression and Random Forest.
Ethereum-based tamper-proof certificate management system for academic credentials, using smart contracts and Web3 integration.
K-means clustering analysis with interactive Tableau dashboards for community financial health assessment programs. Published at ICT4DA 2024.
Machine learning model that predicts laptop prices from key specs like model, RAM, storage type, GPU, CPU, IPS display, and touch screen. Compared Linear Regression, KNN, Decision Trees, and Random Forest; Random Forest achieved the best performance with an R2 score of 0.86.
Peer-reviewed research in machine learning, NLP, and applied data science.
From academic research to production engineering across three continents.
Open to freelance projects, remote roles, and research collaborations. Based in Nairobi — working globally.
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