Jiajia H

About

I work on products at the intersection of AI infrastructure, data quality, and human-in-the-loop systems. My focus is on building reliable workflows that combine automation, evaluation, and expert judgment to improve model performance and scale high-quality data operations. My background spans HCI, UX research, and technical product development, which makes me comfortable navigating ambiguous problems, prototyping quickly, and working deeply with technical teams. I thrive in 0→1 and 1→N environments—clarifying ambiguous problem spaces, designing measurable quality frameworks, aligning stakeholders, and driving execution across engineering, design, and ops. I care about building the foundational tooling that helps teams train safer, more accurate, and more trustworthy models. Recently, I’ve led work across AutoQA systems, LLM-based evaluators, AIGC detection, fraud and identity verification, worker quality signals, and human QA routing. I partner closely with engineering, ML, design, and operations to define problem spaces, align on metrics, and ship systems that improve precision, recall, throughput, and cost efficiency for large-scale AI pipelines. Interests: data governance, LLM

Experience

Education