Jetze Schuurmans
AI Platform Engineer
Rotterdam, South Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolJetze Schuurmans is an AI Platform Engineer with nine years of experience turning ML research into production-grade systems, currently scaling AI4Science platforms at CuspAI. He blends a strong research background in computer vision, NLP and tensor methods from TU Delft with hands-on MLOps expertise—building cloud-native pipelines, evaluation frameworks and GenAI deployments for enterprises like ING. Known for bridging academia and industry, he has published research while also designing AWS architectures and teaching Production-Ready Python and ML Systems Design. He’s advised investors via technical due diligence on AI-first startups, revealing a knack for assessing technical maturity beyond model performance. Based in Rotterdam, he merges econometrics training with practical engineering to deliver reproducible, scalable ML solutions for science and industry.
9 years of coding experience
7 years of employment as a software developer
Minor Mergers and Aquisitions Psychology Economics, Minor Mergers and Aquisitions Psychology Economics at Carleton UniversityMaster of Science (M.Sc.) Econometrics and Management Science, Master of Science (M.Sc.) Econometrics and Management Science at Erasmus University Rotterdam
English, Dutch, German, r, matlab
Stackoverflow
21reputation
0reached
1answer
0questions
Github Skills (47)
python10
data-science10
pandas10
3d-object-detection10
data-structure10
data-structures10
data-analysis10
point-cloud9
object-detection8
bots8
data-stream7
pytorch7
openmmlab7
image-segmentation7
bot-framework7
Programming languages (4)
Github contributions (5)
godatadriven/mac-install
Mar 2023 - Sep 2025
Setting up your new Macbook with an install script.
Contributions:1 PR, 15 pushes, 1 comment in 2 years 5 months
install-script
JSchuurmans/MScThesis
Oct 2018 - Aug 2019
Master Thesis Econometrics - Intent Classification with Bayesian Neural Nets
Contributions:2 PRs, 18 pushes, 3 branches in 9 months
bayesianeconometricsintent-classification
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