Frédéric Rechtenstein
Switzerland
Summary
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Rockstar🎓
Top SchoolFrédéric Rechtenstein is a software engineer based in Switzerland with 8 years of experience building distributed systems, embedded software, machine learning pipelines, and DevOps automation. He combines hands-on ML engineering with production-focused DevOps, notably contributing to TensorFlow Model Optimization by improving CI/CD, hardening tests, and adding pruning tools for Keras models. Comfortable across low-level embedded constraints and cloud-native deployment, he focuses on making ML models reliable, reproducible, and efficient in production. Trained at KAIST, he brings a research-minded approach to practical engineering problems and a knack for tightening test and release workflows that quietly reduce incidents and speed delivery.
8 years of coding experience
Korea Advanced Institute of Science and Technology
French, English, Korean, German
Stackoverflow
61reputation
2kreached
9answers
0questions
Github Skills (20)
python10
machine-learning10
cicd10
model-compression10
keras10
pruning10
tensorflow10
optimization10
testing9
dockers9
docker9
build-automation9
bazel9
mlops9
quantization9
Programming languages (3)
Github contributions (5)
tensorflow/model-optimization
Apr 2021 - May 2022
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
Role in this project:
ML Engineer & DevOps Engineer
ML Engineer & DevOps EngineerContributions:2 releases, 6 reviews, 28 commits in 1 year
Contributions summary:Frédéric primarily focused on improving the testing and deployment of the model optimization toolkit. Contributions include assigning bug numbers to TODOs, refactoring tests to reuse test utilities, and adding a smoke test to verify installation and import. Additionally, the user implemented CI/CD improvements like making CI scripts more strict, gathering test logs, and allowing Git repo location specification, enhancing the automated build process. The user also added API and command-line tools to prune Keras models.
ml-modelspythonquantized-networkstensorflowsparsity
fredrec/model-optimization
Dec 2021 - Dec 2021
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
Contributions:8 pushes in 1 day
ml-modelspythonfairness-mldeep-learningdeployment
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