Machine Learning Data Engineer with 7+ years of experience building production ML pipelines, deploying LLMs, and architecting cloud-native data solutions on AWS. From fine-tuning transformers to leading cross-continental data science teams.
I'm a Machine Learning Data Engineer based in Nairobi, Kenya, specializing in building end-to-end AI systems — from raw data ingestion to production-grade model deployment.
My work spans LLM fine-tuning, MLOps pipeline design, cloud-native ETL/ELT architectures, and real-time data processing. I've deployed systems for government bodies, NGOs, and enterprise clients across Africa, Asia, and the Americas.
Beyond engineering, I am passionate about knowledge transfer — I've trained 350+ data scientists and engineers across Tanzania, Nepal, Bhutan, and Kenya, and co-authored a Master's curriculum adopted by Collège de Paris.
LLM-powered mental health chatbot fine-tuned on transformer models, with a full data pipeline for continuous retraining. Adopted by the Bhutanese Government to enhance the Gross National Happiness Index.
Scalable data pipeline ingesting Sentinel-2 satellite imagery and APIs to detect flood, fire, and earthquake events. Deployed on AWS and presented to the United Nations.
Real-time embedded analytics platform tracking NPS, CSAT, CES, CLV, and Churn Rate for enterprise clients. Migrated ETL pipeline to AWS with live reporting to client sites.
ML system trained with 120 Nepalese students to identify early causes of Chronic Obstructive Pulmonary Disease in Kathmandu province using climate and health data.
CI/CD MLOps infrastructure using mlflow, Docker, Kubernetes, and AWS CodePipeline — reducing time-to-market for AI solutions by 45% through automated deployment and monitoring.
Co-designed and implemented a Master's in Data Science curriculum covering data engineering, ML, analytics, and cloud computing — now officially adopted by Collège de Paris.
Open to full-time remote roles, consulting projects, and speaking engagements in AI, Data Engineering, and ML.