Giacomo Orsi

Machine Learning Engineer at Apple

Barcelona, Catalonia, Spain
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Summary

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Senior
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Top School
Giacomo Orsi is a machine learning engineer with 11 years of experience building AI and big-data solutions across industry and academia, currently helping bring Apple Intelligence to global languages. His background spans research roles at MIT Senseable City Lab and AMS Institute applying ML to urban mobility, plus production engineering on search and monitoring systems at Apple and AWS. He has hands-on NLP experience from a stint at the European Central Bank where he developed automated product classification for inflation measurement, and academic credentials from EPFL and the University of Bologna. Comfortable bridging research and production, he pairs large-scale graph and data analysis expertise with practical engineering—one example being his open-source update to a HoloLens visualization toolkit during his Mixed Reality work. Fluent in shifting between prototype research and deployed systems, he operates at the intersection of applied ML, big data infrastructure, and human-centered urban applications.
code11 years of coding experience
job1 year of employment as a software developer
bookBachelor's degree Computer Science for Management, Bachelor's degree Computer Science for Management at Alma Mater Studiorum – Università di Bologna
bookMaster's degree Computer Science specialization in Data Analysis, Master's degree Computer Science specialization in Data Analysis at EPFL
languagesEnglish, French, Italian, German
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Github Skills (17)

pytorch7
graph7
deep-learning7
graph-convolutional-networks7
graph-neural-network7
plist6
swift6
geometric-deep-learning6
ios6
neural-network4
jolie3
vscode3
intellisense3
vscode-extension2
visual-studio-code2

Programming languages (6)

TypeScriptCJolieHTMLJupyter NotebookPython

Github contributions (5)

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giacomoorsi/OpenRitardi

Aug 2023 - Sep 2024

OpenRitardi is the first visualization tool of train delays in Italy. You can see the performance of each station and train, and see where the railway service can be improved. The project showcases how open data allows accountability and improves quality of service.
Contributions:2 releases, 9 reviews, 19 PRs in 1 year 1 month
Contributions:3 commits, 2 pushes, 1 branch in 26 days
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