Summary
Liangjun Song is a Machine Learning Engineer based in Melbourne with 13 years of experience building production ML systems and data platforms. He has driven search and recommendation improvements, fraud detection, and content moderation at Redbubble—delivering measurable lifts in CTR and add-to-cart and scaling pipelines for 100M+ events. Now at WiseTech Global and contributing to SGLang, he focuses on making large language and vision models faster and more controllable through co-designed runtime and frontend language work. His background blends academic rigor (PhD candidate at RMIT) with hands-on research internships at Microsoft Research Asia and NUS, spanning speech, web mining, and probabilistic models. A permanent Australian resident who enjoys cross-disciplinary collaboration, he brings both algorithmic depth and practical MLOps experience to turn experimental models into reliable production services. An understated strength is his track record of improving long-tail search relevance and offline evaluation frameworks that reduce experimental risk while boosting business metrics.
13 years of coding experience
1 year of employment as a software developer
Bachelor of Science (BS), Computer and Information Systems Security/Information Assurance, Bachelor of Science (BS), Computer and Information Systems Security/Information Assurance at Harbin Institute of Technology
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at RMIT University