Jesse Sun
Machine Learning Engineer at BetterUp
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolJesse Sun is a Machine Learning Engineer based in Old Toronto with eight years of experience building ML and data platforms, recommendation systems, and high-performance model training pipelines. Comfortable across Rust, C++, and Python, he specializes in distributed systems, systems programming, and performance optimization for PyTorch workloads on HPC and cloud clusters. His research background—published work on deep quantile networks and MICCAI-first‑author papers—reflects a strong foundation in math, combinatorial optimization, and generative models that informs practical production systems. At BetterUp he bridges ML infrastructure and feature-store engineering, drawing on hands‑on experience with Slurm-managed GPU clusters and end‑to‑end data pipelines for medical imaging and time-series forecasting. Notably, Jesse combines rigorous academic research with production-focused engineering, making him adept at turning algorithmic insights into scalable, performant ML services.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Computer Science, Minor in Combinatorics and Optimization, Bachelor of Computer Science, Minor in Combinatorics and Optimization at University of Waterloo
English, Chinese
Github Skills (8)
pdf9
medical-image-segmentation8
segmentation7
densenet6
classification6
pytorch2
llm1
rust1
Programming languages (2)
Github contributions (5)
htt1994/VesselSeg-1
May 2019 - May 2019
DenseNet Parallel Branch Retina (DenseNetPBR) for concurrent segmentation and classification experiments.
Contributions:75 commits in 21 days
classificationdensenetsegmentation
sunjesse/shape-attentive-unet
Jan 2020 - Aug 2021
Code for our paper SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation. https://arxiv.org/pdf/2001.07645v3.pdf published at MICCAI 2020.
Contributions:32 commits, 34 pushes, 1 branch in 1 year 6 months
medical-image-segmentationpdf
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