Summary
Michael Gallimore is a Senior Manager focused on AI upskilling and adoption with eight years of hands-on experience building applied machine learning systems across acoustics, ecology, and finance. He holds a BSc (Hons) in Acoustics and has shipped state-of-the-art birdsong recognition models for Environment and Climate Change Canada, producing open-source tooling and validation workflows to avoid overfitting on real-world audio. Comfortable from signal processing and embedded electronics to PyTorch/TensorFlow model training on cloud or local GPUs, he also boosted a finance app's vendor/category classifier by 40% during a production deployment. An organizer of the ML Squamish study group, he blends community leadership with practical experimentation—examples include a siamese network for whale identification and a CNN web app deployment. Equally at home writing FIR/IIR filters in MATLAB as he is iterating ML experiments with W&B, his profile reflects a rare mix of acoustic domain expertise, CNC machining background, and production-minded data science.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Science (BSc), Acoustics, Bachelor of Science (BSc), Acoustics at The University of Salford
Software Engineering, Software Engineering at Answer.AI
Practical Deep Learning For Coders, Practical Deep Learning For Coders at fast.ai
St. Mary's College, Blackburn
French, English