Raphael Peer
Senior Machine Learning Engineer at Inscribe AI
Stockholm, Sweden
Summary
🤩
Rockstar🎓
Top SchoolRaphael Peer is a Senior Machine Learning Engineer based in Stockholm with 11 years of experience blending backend engineering and applied ML to ship production-ready systems. He has worked across fintech and document automation—driving credit underwriting models and Java-based credit policy implementations at Klarna and building invoice extraction and clustering tools earlier in his career. Currently focused on integrating ML into product at Inscribe AI, he combines model development, performance optimization, and scalable ETL pipelines on AWS. Trained in both data science and molecular biology, he brings a research-driven mindset to practical engineering problems and a knack for bridging domain knowledge with deployable ML solutions. Notably, his background includes computational structural biology and recommender/predictive maintenance projects, reflecting a pattern of applying statistical rigor to diverse real-world problems.
11 years of coding experience
6 years of employment as a software developer
Master of Science - MS Molecular Biology, Master of Science - MS Molecular Biology at University of ViennaMaster of Science - MS Data Science, Master of Science - MS Data Science at Paris Lodron Universität Salzburg
English, German, Swedish
Github Skills (8)
scikit10
data-analysis10
statistics10
machine-learning10
python10
data-science10
scikit-learn10
science4
Programming languages (3)
Github contributions (5)
raph333/Consensus-residue-contact-calculator
Aug 2016 - Sep 2019
Contributions:6 releases, 24 pushes, 2 branches in 3 years 2 months
raph333/masters_project
Oct 2019 - Nov 2022
graph neural networks for predicting molecular properties
Contributions:90 pushes, 6 branches in 3 years 1 month
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