Kimonas Sotirchos
Software Engineer at Mistral AI
Athens, Attica, France
Summary
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Rockstar🎓
Top SchoolKimonas Sotirchos is a software engineer with a decade of experience building and operating cloud-native ML infrastructure, currently delivering LLMs and AI Studio on production deployments. He has led Kubeflow’s Notebooks and Manifests working groups—designing core Kubernetes controllers, web apps, and the release/sync processes used by the project—and has been release manager for multiple Kubeflow releases. His background blends full‑stack frontend work (Jupyter notebook UI) with DevOps automation around manifests, GitOps, Istio/OIDC integrations, and large-scale MLOps delivery. At Canonical and Arrikto he combined technical leadership and hands-on engineering to make Charmed Kubeflow production-ready across cloud environments. Based in Athens with an NTUA computer science master’s, he pairs open-source stewardship with pragmatic scripting and automation skills that often hide in release tooling and CI/CD orchestration.
10 years of coding experience
7 years of employment as a software developer
Master's Degree, Computer Science, Master's Degree, Computer Science at National Technical University of Athens
English, Greek
Stackoverflow
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Github Skills (38)
kubernetes10
github-ci10
javascript10
docker10
python10
kustomize10
css10
kubeflow10
typescript10
front10
dockers10
cicd10
automation10
front-end-development10
typescript-types10
Programming languages (16)
Github contributions (5)
kubeflow/manifests
Dec 2019 - Oct 2022
A repository for Kustomize manifests
Role in this project:
DevOps Engineer
DevOps EngineerContributions:9 releases, 164 reviews, 79 commits in 2 years 10 months
Contributions summary:Kimonas primarily focuses on updating and maintaining the deployment manifests for the Kubeflow project. Their contributions involve modifying configuration files, updating image tags, and integrating new components like KFP Tekton and the KServe web app. A significant portion of their work centers around automating the deployment and testing processes, as demonstrated by their scripts for setting up and configuring various Kubeflow components, including those related to e2e tests. They also handle the syncing of manifests from different repositories to ensure the project's consistency and update the README file.
kubeflowk8skuberneteskustomizemanifests
kubeflow/kubeflow
Feb 2019 - Jan 2023
Machine Learning Toolkit for Kubernetes
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:3 releases, 262 reviews, 111 commits in 3 years 11 months
Contributions summary:Kimonas primarily focused on developing the frontend UI for the Jupyter web application, implementing features related to notebook management. Their contributions included the introduction of new frontend components, the implementation of new UI and the refactor of existing ones, and the integration of the frontend with the backend. The user also added support for backend functionality, creating functionalities for handling volumes.
pythondata-sciencenotebookmachine-learningmlops
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