I’m an AI and Machine Learning engineer with hands-on experience in model fine-tuning, dataset engineering, and building scalable data-driven systems. Currently working at the intersection of research and real-world deployment, I focus on turning complex problems into practical, measurable solutions. I’ve worked on improving model performance, designing structured datasets, and optimizing data pipelines to increase efficiency and accuracy. My experience spans applied machine learning, experimentation, and system-level thinking — not just theory. Beyond core ML, I’m deeply interested in generative systems and intelligent automation. I approach every project with a builder’s mindset: clarity in problem definition, precision in execution, and measurable outcomes. If you’re looking to discuss AI systems, model optimization, research pathways, or career direction in ML — I’m happy to connect.