I'm a full-stack ML system builder and AI researcher with a Ph.D. in Deep Learning from Monash University. Over the past decade, I’ve led AI initiatives across startups and academia, designing and deploying intelligent systems that work in the real world. My specialty lies in end-to-end machine learning architecture: from model development to automated training pipelines, CI/CD, scalable deployment, and ongoing monitoring. I thrive at the intersection of deep learning, software engineering, and cloud-native infrastructure, translating cutting-edge research into high-impact AI systems. As co-founder and CTO at a VC-backed startup, I’ve built products from scratch, led engineering teams, and architected cloud-native ML platforms using Kubernetes, Terraform, MLflow, and FastAPI. I’m also KCNA-certified, enabling me to build systems that are both scalable and reliable. Whether you’re building enterprise AI tools, scaling MLOps infrastructure, or translating research into product-ready systems, I’d love to connect, collaborate, or consult on turning complex AI into real-world impact.