Yonatan Shelach
Generative AI Engineer
Israel
Summary
🤩
Rockstar🎓
Top SchoolYonatan Shelach is a Generative AI Engineer and Computer Science student at the Technion with four years of hands-on experience building and deploying ML systems. He spent four years at Iguazio (now part of McKinsey) as a Machine Learning Engineer, and recently joined VAST Data to focus on generative AI in production. Yonatan has contributed to prominent open-source MLOps work—adding remote pipeline scheduling and robustness fixes to the MLRun platform—demonstrating practical experience with CI/CD and production workflow automation. Comfortable across research-adjacent coursework and production engineering, he blends academic rigor from the Technion with real-world MLOps delivery. Notably, his contributions show attention to developer ergonomics and reliability, from CLI test fixes to artifact path handling.
4 years of coding experience
4 years of employment as a software developer
Computer Science, Computer Science, Computer Science, Computer Science at Technion - Israel Institute of Technology
Github Skills (12)
kubernetes10
workflow-automation10
mlops10
workflow-engine10
python10
kubernetes-pods10
cicd9
machine-learning9
rpc9
experiment8
data-science8
data-engineering7
Programming languages (3)
Github contributions (5)
mlrun/mlrun
Jul 2022 - Jan 2023
MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.
Role in this project:
MLOps Engineer
MLOps EngineerContributions:109 reviews, 21 commits, 70 PRs in 5 months
Contributions summary:Yonatan contributed significantly to the MLRun MLOps platform, adding features for remote pipeline scheduling with the `RemoteRunner`. They implemented logic for handling workflow scheduling, including options for overwriting existing schedules. Furthermore, they fixed CLI tests related to project operations. The user also updated the project's documentation, and handled the artifact path for the function runner.
experiment-trackingpythondata-sciencecmlmachine-learning
yonishelach/mlrun
May 2022 - Aug 2024
Machine Learning automation and tracking
Contributions:557 pushes, 73 branches in 2 years 3 months
pythondata-sciencemachine-learningtrackingautomation
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