Nathasya Utami Hakim

Applied AI Engineer with 2 years of hands-on experience building end-to-end machine learning and LLM-powered systems, with a focus on Retrieval-Augmented Generation (RAG), Computer Vision, and production-oriented AI workflows. Experienced in developing multimodal AI pipelines using EfficientNetB5, FAISS, LangChain, and quantized LLM inference with Qwen and LLaMA models. Key achievements include developing a brain tumor classification system that achieved 96.82% recall through systematic hyperparameter optimization, publishing research at IEEE ICICoS 2025, and architecting a multimodal RAG system capable of generating structured clinical reports from MRI scans using medical knowledge retrieval. Currently looking for remote opportunities as an AI Engineer, Machine Learning Engineer, or LLM/RAG Engineer where I can contribute to building practical AI products, scalable inference systems, and intelligent workflows that solve real-world problems.