Yusuf Adelakun

I’m a Machine Learning Engineer focused on turning research-level ideas into production-ready systems. I build ML pipelines, evaluate model quality, and improve response performance with techniques like advanced prompt engineering and structured outputs.

In my recent roles, I’ve developed and deployed scalable machine learning solutions using Docker and FastAPI, including audio classification pipelines and AI engine features spanning computer vision and natural language processing. I also work on end-to-end services that improve efficiency—like reducing manual review time by ~40% and ~60% in deployment-focused projects.

I enjoy building practical applications such as FastAPI-served prediction APIs, Conversational RAG systems with PDF support (ChromaDB), emotion classification using a Vision Transformer, and AI-assisted email processing with local LLMs (Ollama). My professional ethos is clean engineering: solid preprocessing, reliable pipelines, and measurable improvements that users can feel.