CHUANLIU.

I studied Computer Science and Statistics at the University of Toronto, two disciplines with one obsession underneath: how do you make machines reason from data?

At Apple, I built backend infrastructure that real people depended on. I learned what it means to ship software at that scale, the refactoring discipline, the weight of access control in a system handling sensitive data, the gap between "it works" and "it works at scale." That's where I learned that software has consequences, and that the engineers who forget that are usually the ones who cause them.

At OpenJobs AI, I built Mira, an autonomous recruiter that sources, engages, and closes candidates end-to-end, without a human in the loop. Underneath: a retrieval and reranking pipeline at 95% matching accuracy, multi-model orchestration, agent workflows that make decisions and act on them, running across millions of records. The first AI in recruiting that doesn't assist. It decides.

What I build is not "AI that answers questions." It is systems that understand goals, operate in the world, and get better from every mistake. That's the only problem worth solving.