Shawn Carere is a Machine Learning Engineer with eight years of experience building AI infrastructure and production ML systems, currently contributing to Spotify’s Machine Learning Platform team. He holds an MSc from the University of Toronto (Ontario Graduate Scholarship) and a BASc in Electrical Engineering from Queen’s, where he graduated top of his class. Shawn has designed and deployed self-hosted LLM inference platforms using Kubernetes, vLLM, Ray, and observability stacks, and developed in-house model quantization and sparsification tooling to boost throughput. His background spans applied research in medical imaging—integrating nnUNetv2 into federated pipelines and shipping DICOM-compatible segmentation services—and production-facing systems such as sybil detection APIs and CI/CD automation. Notably, he has a track record of translating cutting-edge research into reliable, deployable services that bridge clinical, research, and industry needs.
8 years of coding experience
3 years of employment as a software developer
Master of Science - MSc, Master of Science - MSc at University of Toronto
Bachelor of Applied Science - BASc - First Class Honours Electrical Engineering, Bachelor of Applied Science - BASc - First Class Honours Electrical Engineering at Queen's University
Ashbury Bilingual Diploma & Ontario High School Diploma Sciences, Ashbury Bilingual Diploma & Ontario High School Diploma Sciences at Ashbury College
Intelligent Heart Monitoring System (IHMS) for real-time arrhythmia detection - Queen's University ELEC490 Capstone Project
Contributions:8 PRs, 57 pushes, 8 branches in 5 years 3 months
queencapstonereal-timeheart-monitoringheart
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Shawn Carere - Machine Learning Engineer at Spotify