Liangjun Song

Machine Learning Engineer at WiseTech Global

Melbourne, Victoria, Australia
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Summary

👤
Senior
🎓
Top School
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.
code13 years of coding experience
job1 year of employment as a software developer
bookBachelor 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
bookDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at RMIT University
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Github Skills (8)

cuda10
llama10
pytorch10
inference10
llm10
transformer9
counting4
ffmpeg2

Programming languages (1)

Python

Github contributions (5)

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Contributions:10 pushes, 1 branch in 3 years 2 months
lycanlancelot/sglang

Jan 2025 - Mar 2025

SGLang is a fast serving framework for large language models and vision language models.
Contributions:15 pushes, 2 branches in 1 month
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