MLOps.community Packaging MLOps Tech Neatly for Engineers and Non-engineers // Jukka Remes // #322
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Jun 10, 2025 Jukka Remes, a Senior Lecturer and AI Architect, shares insights from his extensive experience in MLOps and AI enablement. He discusses the creation of an open-source MLOps platform designed for flexibility across environments, emphasizing the importance of user-friendly tools for both engineers and non-engineers. Jukka also addresses the challenges of transitioning models from research to production, highlights the need for compliance with evolving regulations, and advocates for collaboration to bridge gaps between technical teams and stakeholders.
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Origin Story of MLOps Platform
- Jukka Remes developed an open-source MLOps platform initially at Silo AI for client cases ranging from outsourcing ML development to mature clients building their own platforms.
- This platform includes pipeline orchestration, model management, deployment, and some monitoring components covering the full ML lifecycle.
Platform Supports Diverse Models
- The open-source MLOps platform is designed to support all kinds of models but may require extra work for exotic use cases like federated learning.
- The platform includes widely used tools like Kubeflow, MLflow, and KServe which are generic and flexible.
Early Research Challenges Shape Vision
- Jukka Remes shares early experience managing complex research analytics on brain imaging data without modern tools, highlighting the tediousness and importance of consistency in research workflows.
- These experiences inspired his appreciation for modern MLOps stacks to increase quality and trust in scientific results.