I don’t just build AI models — I build AI systems that work in real-world conditions. AI Engineer with a focus on turning ideas into scalable, production-ready pipelines, not just experiments. My work sits at the intersection of: - Machine Learning & Deep Learning - Retrieval-Augmented Generation (RAG) - NLP & Computer Vision systems I’ve built end-to-end solutions including: - OCR-driven Visual Question Answering (VQA) pipelines - Text summarization systems for real-world data - Retrieval systems using FAISS and modern embedding models Tech stack: Python | PyTorch | TensorFlow | FastAPI | Docker | Hugging Face What differentiates my work: I focus on what happens after the model — retrieval quality, system design, scalability, and making AI usable beyond demos. If you're building AI systems that need to be reliable, efficient, and deployable — we’re solving the same problems.