Machine Learning Engineer, Medical Devices at SandboxAQ
Edmonton, Alberta, Canada
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Summary
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Senior
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Top School
John Maidens is a machine learning engineer specializing in biosignal analysis with 13 years of experience building regulated medical-device software and ML-driven sensing products. He has led end-to-end ML and DSP efforts—from real-time C DSP on mobile apps to cloud-deployed TensorFlow models—helping ship 510(k)-cleared heart sound and ECG SaMD at Eko and contributing to Apple’s optical heart rate sensing. More recently he led sleep-health ML at Eight Sleep and now develops models for a quantum magnetocardiography device at SandboxAQ, blending classical signal processing with cutting-edge sensor modalities. He holds a PhD in EECS from UC Berkeley and brings a rare combination of clinical study design, regulatory productization, and hands-on algorithm implementation. Notably, he secured over $3M in NIH SBIR funding as PI and authored peer-reviewed papers and patents on ML-based heart sound analysis. Based in Edmonton, he pairs deep technical rigor with cross-functional leadership in hardware-software-clinical teams.
12 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Electrical Engineering and Computer Sciences, Doctor of Philosophy (Ph.D.) Electrical Engineering and Computer Sciences at University of California, Berkeley
Bachelor of Science (BSc) Mathematics, Bachelor of Science (BSc) Mathematics at University of Alberta
Master's Degree Biomedical Engineering, Master's Degree Biomedical Engineering at The University of British Columbia
Contributions:2 commits, 1 push, 1 branch in 1 day
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John Maidens - Machine Learning Engineer, Medical Devices at SandboxAQ