Summary
Gary Mulder is a hybrid Data Scientist and Engineer with 11 years of experience designing end-to-end ML solutions and data architectures that turn complex business problems into measurable outcomes. He specializes in NLP and large language models, including hands-on fine-tuning of multi‑billion parameter models and practical LORA adaptations, and applies GPU-accelerated toolchains (HuggingFace, MXNet, XGBoost) for production workloads. His background spans time series meta-learning and ensemble forecasting, unsupervised clustering, advanced feature selection, and black-box interpretability, supported by strong data engineering and cloud GPU architecture skills across AWS, GCP and IBM. Gary has operational pedigree from roles in finance, gaming, and enterprise consulting and contributes to open-source ML tooling—adding model download automation, Docker integration and CLI/version checks to a popular llama.cpp Python binding. Based in Limassol, Cyprus, he pairs deep technical curiosity (from low-level C to modern DevOps) with a track record of delivering scalable, performant systems that bridge research and production.
11 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Bachelor of Science - BS at University of Otago
Postgraduate Degree, Postgraduate Degree at University of Liverpool
Time Series Forecasting in R, Time Series Forecasting in R at Eindhoven University of Technology
Hadley Wickham Master Class in R, Hadley Wickham Master Class in R at RStudio
English