Joris Mollinga
AI Engineer at Joris Solutions
Amsterdam, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolJoris Mollinga is a freelance machine learning engineer based in Amsterdam with a decade of professional experience and 5+ years focused on computer vision alongside 2 years working with generative AI. He combines hands-on model development—preferencing PyTorch—with production deployment expertise on AWS, from containerized APIs to pipelines. As co-founder and former CTO of DuckDuckGoose AI he built and led delivery of a deepfake detection product, extending it to synthetic audio/video and owning dataset creation and maintenance. His background includes research roles producing published work in medical imaging and molecular synthesis, reflecting a strong bridge between fundamental research and product engineering. He also brings entrepreneurial pragmatism from running his own consultancy, where recent projects span LLM fine-tuning, network compression, graph neural networks, and agent work in LangGraph and PydanticAI. Unexpectedly, his academic path from aerospace engineering to an MSc in Artificial Intelligence underpins a systems-minded approach to ML problems.
10 years of coding experience
7 years of employment as a software developer
MSC, Artificial Intelligence, MSC, Artificial Intelligence at University of AmsterdamBSC, Luchtvaart- en ruimtevaarttechniek, BSC, Luchtvaart- en ruimtevaarttechniek at Delft University of Technology
Dutch, English
Github Skills (15)
python8
gpu7
machine-learning7
deep-learning7
pytorch6
artificial-intelligence6
numpy5
neural-network5
synthesis3
gpu-acceleration3
tensor3
autograd2
amdgpu1
inference1
nvidia1
Programming languages (2)
Github contributions (5)
mishastassen/g7
Nov 2015 - Jan 2016
Contributions:183 pushes, 10 comments, 52 issues in 2 months
sara-nl/attention-sampling-pytorch
May 2020 - Dec 2020
This is a PyTorch implementation of the paper: "Processing Megapixel Images with Deep Attention-Sampling Models".
Contributions:3 commits, 16 pushes, 6 comments in 7 months
pytorchmachine-learningartificial-intelligenceattention-samplingpytorch-implementation
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