Charlene 梁巧玲 is a Senior Machine Learning Engineer with eight years' experience building applied research and production ML systems across healthcare, energy, and enterprise platforms. She has led end-to-end MLOps, research-to-production pipelines and cloud migrations—bridging rapid prototyping with robust, cost-conscious deployments at companies like harrison.ai, nbn and Relevance AI. Her work spans deep learning, RAG/agentic systems, time-series forecasting, and model lifecycle automation, and she brings hands-on experience with serverless inference, model distillation and multi-cloud platform engineering. Equally comfortable with technical strategy and cross-functional leadership, she focuses on sociotechnical system design that scales while prioritising interpretability and ethical AI. Based in the UK, she combines an R&D mindset with product delivery instincts and an uncommon background in mechatronics and fieldwork that informs her systems thinking and practical experimentation.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Engineering - BE (Hons) Electronics and Computer Systems Engineering (Mechatronics), Bachelor of Engineering - BE (Hons) Electronics and Computer Systems Engineering (Mechatronics) at Victoria University of Wellington
Deep Learning Summer School, Deep Learning Summer School at Tsinghua University
Oxford ML Summer School, Oxford ML Summer School at University of Oxford
Climate Change: Learning for Action, Climate Change: Learning for Action at Terra.do
Summer School Deep Learning for Climate Change, Summer School Deep Learning for Climate Change at Climate Change AI
Contributions:8 PRs, 12 pushes, 2 branches in 5 years 6 months
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Charlene 梁巧玲 - Senior Machine Learning Engineer at OVO