I build data-intensive and AI-powered systems, with a focus on Python, machine learning, NLP, LLMs, data engineering, and low-resource language technologies.
My background spans software engineering, data science, machine learning research, and production data systems. I enjoy turning research and data into reliable, reproducible, and useful software.
- π€ AI/ML: NLP, Transformers, LLMs, ASR
- π Programming: Python, SQL, R
- ποΈ Data Engineering: BigQuery, Spark, PySpark, ETL/ELT
- π§ NLP: Low-resource & multilingual language technologies
- π AI Evaluation: Model benchmarking and evaluation
- βοΈ Engineering: APIs, Docker, Git/GitHub, CI/CD
- π Data: PostgreSQL, analytics and visualization
End-to-end data engineering and analytics work focused on transforming lending data into actionable customer intelligence.
Fine-tuning and evaluation of Wav2Vec 2.0 for automatic speech recognition in Kikamba, a low-resource African language.
Work on evaluating language models for African languages, with a focus on low-resource and multilingual NLP.
Transformer-based part-of-speech tagging for African languages using modern NLP techniques.
I'm particularly interested in building:
- AI-powered applications
- LLM and NLP systems
- Intelligent data platforms
- Low-resource language technologies
- Machine learning infrastructure
- Reliable and reproducible AI systems
π« Open to: AI Engineering, Software Engineering, Data Engineering, ML Engineering, and NLP/LLM opportunities.
