Packaging MLOps Tech Neatly for Engineers and Non-engineers // Jukka Remes // #322

Packaging MLOps Tech Neatly for Engineers and Non-engineers // Jukka Remes // #322

Author: Demetrios June 10, 2025 Duration: 55:30

Packaging MLOps Tech Neatly for Engineers and Non-engineers // MLOps Podcast #322 with Jukka Remes, Senior Lecturer (SW dev & AI), AI Architect at Haaga-Helia UAS, Founder & CTO at 8wave AI.


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// Abstract

AI is already complex—adding the need for deep engineering expertise to use MLOps tools only makes it harder, especially for SMEs and research teams with limited resources. Yet, good MLOps is essential for managing experiments, sharing GPU compute, tracking models, and meeting AI regulations.


While cloud providers offer MLOps tools, many organizations need flexible, open-source setups that work anywhere—from laptops to supercomputers. Shared setups can boost collaboration, productivity, and compute efficiency. In this session, Jukka introduces an open-source MLOps platform from Silo AI, now packaged for easy deployment across environments. With Git-based workflows and CI/CD automation, users can focus on building models while the platform handles the MLOps.


// Bio

Founder & CTO, 8wave AI | Senior Lecturer, Haaga-Helia University of Applied SciencesJukka Remes has 28+ years of experience in software, machine learning, and infrastructure. Starting with SW dev in the late 1990s and analytics pipelines of fMRI research in the early 2000s, he’s worked across deep learning (Nokia Technologies), GPU and cloud infrastructure (IBM), and AI consulting (Silo AI), where he also led MLOps platform development.


Now a senior lecturer at Haaga-Helia, Jukka continues evolving that open-source MLOps platform with partners like the University of Helsinki. He leads R&D on GenAI and AI-enabled software, and is the founder of 8wave AI, which develops AI Business Operations software for next-gen AI enablement, including regulatory compliance of AI.


// Related Links

Open source-based MLOps k8s platform setup originally developed by Jukka's team at Silo AI - free for any use and installable in any environment from laptops to supercomputing: https://github.com/OSS-MLOPS-PLATFORM/oss-mlops-platform

Jukka's new company: https://8wave.ai


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Timestamps:

[00:00] Jukka's preferred coffee

[00:39] Open-Source Platform Benefits

[01:56] Silo MLOps Platform Explanation

[05:18] AI Model Production Processes

[10:42] AI Platform Use Cases

[16:54] Reproducibility in Research Models

[26:51] Pipeline setup automation

[33:26] MLOps Adoption Journey

[38:31] EU AI Act and Open Source

[41:38] MLOps and 8wave AI

[45:46] Optimizing Cross-Stakeholder Collaboration

[52:15] Open Source ML Platform

[55:06] Wrap up


Hosted by Demetrios, MLOps.community is a space for honest, meandering talks about the real work of making artificial intelligence systems actually work. This isn't about hype or theoretical papers; it's about the messy, practical, and often surprising journey of taking models from a notebook into a live environment. You'll hear from engineers and practitioners who are in the trenches, discussing the tools, the frustrations, and the occasional breakthroughs that define the day-to-day. The conversations are deliberately relaxed, covering everything from traditional machine learning pipelines to the new world of large language models and even the intangible "vibes" of team culture and process. Each episode peels back a layer on what "production" really means, whether that involves deploying a predictive service, managing an agentic system, or maintaining reliability as everything scales. Tuning into this podcast feels like grabbing a coffee with colleagues who aren't afraid to dig into the technical nitty-gritty while keeping the tone conversational and accessible. It's for anyone who builds, manages, or is just curious about the operational backbone that allows AI to deliver value, offering a grounded perspective often missing from the broader conversation.
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