Summary
Matthew Leung is a Machine Learning Engineer based in Hong Kong with 8 years of experience building and tuning cloud-native, distributed data and ML systems. He has deep cross-domain expertise in performance tuning, root-cause analysis, and capacity planning across databases, Java applications, and distributed frameworks like Spark, Dask, Flink and Kubernetes. At HSBC he led end-to-end performance improvements that cut response times and resolved critical production incidents, and he has recently transitioned into ML-focused roles combining DevOps and model tuning. Matthew spends personal time on machine learning competitions and distributed hyperparameter tuning workflows (e.g., Hyperopt with MongoDB on Kubernetes), and he’s interested in accelerating ML through quantum algorithms for matrix computations. Known for a positive, can-do attitude and strong communication across global teams, he thrives on troubleshooting complex, multi-team problems under pressure.
8 years of coding experience
6 years of employment as a software developer
The Chinese University of Hong Kong (CUHK)
English