Kaile Wang
Performance Engineer at NAB
Melbourne, Victoria, Australia
Summary
🤩
Rockstar🎓
Top SchoolKaile Wang is a Performance Engineer at NAB with experience in performance testing, environment management, and load scripting built on a foundation of software and embedded systems development. With hands-on skills across C++, Java (Spring Boot and Android), Python, and JavaScript (Vanilla/Vue), Kaile bridges backend, frontend and automated testing workflows to diagnose and optimize application performance. Early internships at NAB focused on SIT and automation (Selenium, WDIO) and LoadRunner-based regression testing, giving practical experience from deployment to reporting. Academically grounded with a Master’s in IT from the University of Melbourne and dual degrees from RMIT in Computer Science and Computer Systems Engineering, Kaile also published research on musical instrument recognition as first author. Outside of day-to-day work they maintain hobbyist expertise in embedded firmware, IoT (PCB and LoRa), and signal processing, which informs a pragmatic systems-level perspective on performance. Colleagues describe Kaile as detail-oriented, technically curious, and effective at turning complex test findings into actionable improvements.
2 years of coding experience
3 years of employment as a software developer
The University of MelbourneBachelor of Computer Science, Software development, GPA 3.8/4, Bachelor of Computer Science, Software development, GPA 3.8/4 at RMIT University
Github Skills (4)
multimodal10
large-language-models10
chameleon10
rlhf10
Programming languages (1)
Github contributions (5)
dog-wwwkl/align-anything-kaile
Sep 2024 - Mar 2025
Contributions:7 pushes, 5 branches in 6 months
dog-wwwkl/lmm-r1
Mar 2025 - Mar 2025
Extend OpenRLHF to support LMM RL training for reproduction of DeepSeek-R1 on multimodal tasks.
Contributions:2 pushes in 13 days
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