Matthew Chang is an AI Prompt Engineer and soon-to-be UC Irvine graduate with nine years of hands-on experience building scalable full-stack systems, data pipelines, and production ML infrastructure. He has driven measurable impact across internships at Apple and Partner Evaluation Advisors—cutting Kubernetes deployment time by 98× with a Go CLI and accelerating PDF parsing tenfold via a RAG-powered pipeline. Comfortable owning projects end-to-end, Matthew blends SRE practices, observability (Prometheus/Grafana), and CI/CD automation to reduce downtime and ramp-up time in fast-paced teams. His work spans distributed backend systems, distributed ML pipelines, and data engineering, informed by practical model fine-tuning and prompt evaluation across multiple AI models. Beyond code, he has a track record of translating research ideas into production (3× throughput in 3D preprocessing, 70% calibration improvement) and a knack for shipping tooling that saves teams time. Based in Cerritos, CA, he’s seeking new grad roles for 2026 where he can continue applying infrastructure-first thinking to real-world problems with social impact.
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Matthew Chang - AI Prompt Engineer at DataAnnotation