Yassine Mahjoub

I’m a recent IT engineering graduate with a Data Science specialization, and I focus on turning applied NLP and LLM ideas into production-ready systems. My end-to-end graduation project delivered a Retrieval-Augmented pipeline that matches candidates to job descriptions using hybrid search and modern model tooling.

In my end-of-studies internship (PFE), I designed a retrieval-augmented candidate-screening system, combining BM25 keyword search with dense semantic embeddings. I implemented hybrid retrieval over Elasticsearch and MongoDB to improve ranking relevance, and I built NLP pipelines with HuggingFace Transformers and Word2Vec to compute semantic similarity.

I also engineered the full system logic: a multi-factor scoring approach weighing experience, skill coverage, and education against the semantic match score. To make it deployable and secure, I exposed it through a FastAPI backend with OAuth2/JWT authentication and Dockerized the full stack.

Before that, I built solid Python/SQL foundations through part-time ERP development, customizing Odoo modules and debugging PostgreSQL performance. I’m now actively seeking a junior AI/GenAI engineering role where I can keep building applied NLP and LLM systems that are reliable, measurable, and ready for real users.