Arthur Jenoudet
San Francisco, California, United States
Summary
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Rockstar🎓
Top SchoolArthur Jenoudet is a software engineer specializing in distributed systems and ML infrastructure, currently at Databricks with prior experience scaling Alluxio’s data orchestration platform to handle millions of requests and petabytes of data. He holds an MS in Computer Science & Engineering from the University of Michigan and has a track record of performance-driven systems work—90% faster snapshotting for a Raft-based journal and a 70% metadata size reduction via RocksDB tuning. Arthur contributes to prominent open-source ML tooling, enhancing MLflow with secure presigned URL support and Unity Catalog integration for robust artifact management. Comfortable across Go, Java, Python, and cloud storage integrations, he blends production-grade engineering with practical research instincts and a knack for automating reliability and testing at scale.
2 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Computer Science, 3.65, Bachelor of Science - BS, Computer Science, 3.65 at University of MichiganMaster of Science - MS, Computer Science & Engineering, 3.77, Master of Science - MS, Computer Science & Engineering, 3.77 at University of Michigan College of EngineeringHigh School Diploma, Scientific Concentration, High School Diploma, Scientific Concentration at Cité Scolaire Internationale de Lyon
English, French
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
machine-learning10
databricks10
model-management10
mlflow10
python10
ml-deployment9
ai9
continuous-deployment9
Programming languages (1)
Github contributions (2)
mlflow/mlflow
Jan 2024 - Jan 2025
Open source platform for the machine learning lifecycle
Role in this project:
ML Engineer
ML EngineerContributions:33 reviews, 21 PRs, 10 pushes in 1 year
Contributions summary:Arthur primarily contributed to the development of presigned URL functionality for uploading and downloading model artifacts, focusing on Databricks Unity Catalog integration. Their work involved modifying code related to artifact repositories, particularly for cloud storage like Azure Data Lake and S3, ensuring secure access to model artifacts. The commits also include credential refresh mechanisms to extend the lifetime of access to the model artifacts, and the renaming of registered models. Overall, the user focused on enhancing model management features within the MLflow framework.
pythonlifecyclemlmachine-learningincremental-learning
artjen/mlflow
Feb 2024 - Jan 2025
Open source platform for the machine learning lifecycle
Contributions:71 pushes, 25 branches in 11 months
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