Niels Boom is an MLOps engineer with an MSc in Computing Science and eight years of experience building and productionalizing ML systems and data platforms. He has moved machine learning projects from research to production across Kubernetes, Airflow, Kafka and cloud providers (AWS → Azure), combining software engineering, data engineering and model ops. At Promaton and previously RTL he focused on CI/CD, containerized deployments, GitOps and observability using tools like Helm, Argo, Prometheus and Grafana. Comfortable in Python and Go, he’s shipped end-to-end pipelines integrating Spark, Snowflake and Databricks, and has a practical knack for migrating complex workloads between clouds. His GitHub shows hands-on projects (including a recurring-content detector from his graduation work), reflecting a builder’s mindset that balances reproducibility with pragmatic engineering.
8 years of coding experience
4 years of employment as a software developer
Master of Science (MSc), Computing Science (Data Science specialisation), Master of Science (MSc), Computing Science (Data Science specialisation) at Radboud Universiteit Nijmegen
Bachelor of Science (BSc), Computer Science (Technische Informatica), Bachelor of Science (BSc), Computer Science (Technische Informatica) at Universiteit Twente
Pre-university education (VWO Gymnasium), Pre-university education (VWO Gymnasium) at Ludger College
Helm chart repository for the new unified way to deploy ClearML on Kubernetes. ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
Contributions:1 review, 5 commits, 5 PRs in 7 months
Contributions:2 releases, 16 PRs, 80 pushes in 1 year
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