Victor Shia is a Senior Machine Learning Engineer with 11 years of experience building production ML/AI systems that turn messy enterprise data into reliable decision-making pipelines. With a PhD from UC Berkeley in EECS, he blends rigorous research in state estimation and control with hands-on engineering—leading cross-functional teams and owning architecture, CI/CD, and 24/7 production reliability. At The Human Diagnosis Project he scaled clinical AI that processed millions of cases using hierarchical clustering and LLM-assisted evaluation, and now applies the same pattern to revenue recovery and supplier data reconciliation. He’s equally comfortable writing models, APIs, and deployment tooling (Python, Kubernetes, GCP) and translating a single expert’s tacit knowledge into agentic systems that automate mechanical work. Notably, he has five years of academic teaching and mentorship experience, bridging theoretical control frameworks to real-world autonomous systems and student-built products.
11 years of coding experience
18 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Electrical Engineering and Computer Sciences, Doctor of Philosophy (Ph.D.), Electrical Engineering and Computer Sciences at University of California, Berkeley
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