Olivier Grisel
Vannes, Brittany, France
Summary
🤩
Rockstar🎓
Top SchoolOlivier Grisel is a senior machine learning engineer with 17 years of experience, a long-time core contributor to scikit-learn and a founding engineer at :probabl. who bridges research-grade algorithms and production-ready infrastructure. He balances hands-on ML model work—ranging from convolutional networks for image tasks to scalable parallel pipelines—with deep contributions to Python ecosystem tooling such as joblib, cloudpickle, manylinux/auditwheel and OpenBLAS. A frequent conference speaker and MOOC instructor, he also organizes PyData Paris and crafts tutorials that make complex predictive modeling accessible. His open-source impact spans bug fixes to performance and CI improvements, showing a rare mix of algorithmic insight and systems-level engineering. Based in Vannes, France, he combines academic training from ENSTA and Imperial College with practical experience tuning libraries used across the scientific Python stack. Unexpectedly, his contributions include low-level resilience fixes (pthread_atfork) and CI automation that materially improve reliability for large-scale Python deployments.
17 years of coding experience
19 years of employment as a software developer
MSc. in Advanced Computing, Computer Science, MSc. in Advanced Computing, Computer Science at Imperial College LondonIngénieur, Computer Science, Ingénieur, Computer Science at ENSTAClasses Préparatoires aux Grandes Ecoles, Mathematics and Physics, Classes Préparatoires aux Grandes Ecoles, Mathematics and Physics at Lycée Ste Geneviève
Stackoverflow
39,700reputation
3.9mreached
367answers
6questions
cluster-analysis
top-1%
virtualenv
top-5%
pickle
top-1%
pandas
top-5%
statistics
top-5%
gpu
top-5%
Github Skills (128)
forking10
python10
multithreading10
testing10
pthread10
python-multiprocessing10
ipython10
bash10
c1110
c1710
javas10
duckdb10
deep-learning10
variable-selection10
mnist10
Programming languages (25)
Github contributions (5)
ogrisel/notebooks
Oct 2011 - Sep 2022
Some sample IPython notebooks for scikit-learn
Role in this project:
Data Scientist
Data ScientistContributions:246 commits, 103 pushes in 11 years
Contributions summary:Olivier's contributions involve implementing and experimenting with unsupervised feature extraction techniques, specifically focused on Gaussian mixture models (GMM) and various neural network architectures, particularly an MLP and possibly an autoencoder variant, for the purpose of performing classification tasks on the MNIST dataset. The user is also working on exploring and improving these methods by testing the performance of various optimizers and examining the effects of learning rates on model performance, analyzing the behavior of different configurations. The primary focus is on understanding how well these models generalize to unseen data.
pythondata-scienceipython-notebooksmachine-learningscikit-learn
cloudpipe/cloudpickle
Apr 2015 - Jan 2023
Extended pickling support for Python objects
Role in this project:Back-end Developer & QA Engineer
Back-end Developer & QA EngineerContributions:3 releases, 93 reviews, 147 commits in 7 years 10 months
Contributions summary:Olivier primarily contributed to the `cloudpickle` library, enhancing its functionality and maintainability. They added tests for nested constructs, ensuring comprehensive coverage for various pickling scenarios. The user also performed code style improvements and addressed compatibility issues with PyPy3. Furthermore, they addressed issues related to interactive function pickling, and implemented tests for subprocess-based and memoryview-related tests.
pythonpythonicextended
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