Summary
Ming Liu is a machine learning engineer based in San Francisco with nine years of experience building applied AI systems across startups, academia, and hardware-constrained products. He has shipped end-to-end solutions from LLM backends and AWS-integrated services to on-device computer vision for an AI-powered webcam, and recently contributed to acoustic-based cadence research accepted at ACM CPS-IoT Week. Comfortable moving between Python, C++, embedded deployment, and cloud services, Ming has a track record of optimizing performance (e.g., MATLAB migrations and database speedups) and turning research prototypes into demo-ready products showcased at CES. He blends rigorous academic training from Columbia and UC San Diego with practical, production-focused engineering, and is particularly skilled at extracting high-quality training data and deploying models on low-power hardware.
9 years of coding experience
3 years of employment as a software developer
University of California, San Diego
Master of Science - MS Electrical Engineering, Master of Science - MS Electrical Engineering at Columbia University
Chinese, English