Emmanuel Ameisen
Research Engineer at Anthropic
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolEmmanuel Ameisen is a research engineer at Anthropic with 11 years of experience building and shipping applied machine learning systems across startups and large product teams. Previously a Staff/ Senior ML Engineer at Stripe, he drove a 400% faster model release process and partnered closely with product and design to deploy novel ML features. He authored the O’Reilly book "Building Machine Learning Powered Applications" and contributed practical code for text-analysis pipelines in the companion GitHub repo, reflecting a focus on production-ready ML and model evaluation. Emmanuel’s background spans hands-on deep learning research, AI program leadership at Insight, and production engineering work optimizing operations and deployments, giving him a rare blend of research rigor and delivery-first engineering. He holds advanced degrees across AI, engineering and business from top European and U.S. institutions, and brings a practical curiosity—evidenced by early work from factory floors to courtroom assistance—that informs his human-centered approach to ML.
11 years of coding experience
7 years of employment as a software developer
Mathematics, Physics and Chemistry, Mathematics, Physics and Chemistry at Lycée Henri IVMaster of Science (MSc), Artificial Intelligence, 4.0 GPA, Master of Science (MSc), Artificial Intelligence, 4.0 GPA at Université Paris Sud (Paris XI)Master of Science (M.Sc.), Engineering : Major in Computer Science, 3.7 GPA, Master of Science (M.Sc.), Engineering : Major in Computer Science, 3.7 GPA at University SupélecCorporate Law, Human resources, Management control and Organizations Management, Corporate Law, Human resources, Management control and Organizations Management at Cornell UniversityMaster's degree, Business Administration and Management, General, 3.9 GPA, Master's degree, Business Administration and Management, General, 3.9 GPA at ESCP Europe
Github Skills (6)
machine-learning10
nlp10
python10
text-processing10
scikit-learn9
scikit9
Programming languages (4)
Github contributions (5)
hundredblocks/ml-powered-applications
Nov 2018 - Mar 2020
Companion repository for the book Building Machine Learning Powered Applications
Role in this project:
ML Engineer
ML EngineerContributions:174 commits, 5 PRs, 103 pushes in 1 year 3 months
Contributions summary:Emmanuel's commits primarily focused on implementing and improving an ML-powered application for text analysis. They added sentence separation logic to handle multi-sentence inputs, updated the code to include colorization, and incorporated functions for readability score and model evaluation. Furthermore, they added initial data extraction and exploration pipeline.
machine-buildingpythondata-sciencemachinelearningmachine-learning
hundredblocks/insight-accent
Mar 2017 - Apr 2017
Contributions:50 commits, 45 pushes, 1 branch in 1 month
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