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Qurban Burcuzadə

@qurbanburcuzad

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I build machine learning and RAG systems that turn theory into deployed, measurable products.

Azerbaijan

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What I'm looking for

I'm looking for an intern or entry-level role in machine learning, AI, or data science, ideally in a fully remote, async-friendly environment where I can build practical systems and deepen my technical foundations.

I built VibeMatcher, a cross-domain recommendation engine that maps movies to semantically related books using pretrained embeddings, cosine similarity, genre and mood boosting, and Gemini-generated explanations. It outperformed TF-IDF baselines with a Semantic NDCG@15 of 0.815.

During my deep learning internship at the National Aerospace Agency, I implemented RNN, GRU, LSTM, and Attention architectures in PyTorch while collaborating asynchronously through Slack, Notion, shared documentation, and Git.

I've also built an end-to-end RAG system for scientific PDFs using LangChain, ChromaDB, FastAPI, Docker, Gemini, and Sentence Transformers. I enjoy understanding how systems work beneath the library layer and am looking for an entry-level ML, AI, or data science role.

Experience

Work history, roles, and key accomplishments

Deep Learning Intern

National Aerospace Agency

Feb 2026 - Jun 2026 (4 months)

Studied core sequence modelling architectures and implemented them in PyTorch under the guidance of a PhD researcher, coordinating asynchronously via Slack and shared docs.

PyTorch RNN Git Notion Slack