Dimitris Stafylarakis
Lead Machine Learning Platform Engineer
Amsterdam, North Holland, Netherlands
Summary
🤩
Rockstar🎓
Top SchoolDimitris Stafylarakis is a Lead Machine Learning Platform Engineer based in Amsterdam with 12 years of experience building cloud-native data and MLOps platforms for enterprises like Just Eat Takeaway, KLM and Nike. He combines deep infrastructure and DevOps roots with senior data engineering and MLOps practice, architecting Kubernetes-backed lifecycles for training, serving and monitoring ML at scale. A pragmatic technical lead, he focuses on platform reliability and developer experience while coaching teams to grow engineering maturity. His open-source contributions include practical enhancements to Seldon Core—tuning metric/port configuration and MinIO client setup—reflecting a hands-on approach to productionizing model deployments. Trained as an electrical and computer engineer, he brings both systems-level rigor and real-world delivery across fintech, retail and aviation domains.
11 years of coding experience
13 years of employment as a software developer
Diploma, Electrical Engineering, Diploma, Electrical Engineering at Panepistimion PatronMSc, Computer Engineering, MSc, Computer Engineering at Delft University of Technology
English, Dutch, German, Greek
Github Skills (15)
javas10
machine-learning10
kubernetes10
deploying10
mlops10
gson10
environment-variables10
gitlab-api10
java10
kubernetes-pods10
jenkins-plugin10
python9
webhooks9
go9
testing8
Programming languages (14)
Github contributions (5)
jenkinsci/gitlab-plugin
Jul 2014 - Dec 2014
A Jenkins plugin for interfacing with GitLab
Role in this project:
Back-end Developer
Back-end DeveloperContributions:79 commits, 7 comments, 2 issues in 5 months
Contributions summary:Dimitris primarily focused on enhancing the integration with GitLab, implementing features related to webhooks and merge requests. They modified code to utilize the java-gitlab-api for communication with the GitLab instance and added functionality for filtering incoming triggers based on branch. The user also introduced variables related to source repository in merge request builds and refactored requests to use Gson for serialization.
jenkinsgitlab-apijenkins-plugingitflowjenkins-api-plugin
SeldonIO/seldon-core
Aug 2019 - May 2020
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Role in this project:MLOps Engineer
MLOps EngineerContributions:7 commits, 2 PRs, 21 comments in 8 months
Contributions summary:Dimitris primarily focused on enhancing the Seldon Core framework by modifying and adding features related to metrics and port configurations for machine learning models. Their commits involve adjusting code to use environment variables for metric port names, configuring the MinIO client, and ensuring consistent naming conventions. The changes touch multiple files, including webhook, controller, and test files within the operator directory, indicating a focus on deployment and configuration aspects.
monitorservingdata-sciencedeploymentmachine-learning
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