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​Build a Sovereign AI Factory: an ML Engineer Agent that evaluates, fine-tunes, deploys, and improves open models.
RSVP on Luma for live link: https://luma.com/vfhq98ji

​AI teams are starting to look beyond renting every capability from an external API, they're building systems they own and control. In this hands-on session we'll build exactly that by creating an ML Engineer Agent that will manage a model factory to select and fine-tune the best models for your applications.
RSVP on Luma for live link: https://luma.com/wy08j2yx

​We'll start with a walkthrough where we build an agent that evaluates open models in parallel, fine-tunes promising candidates, deploys the winner, and retrains automatically when performance drops. Think of it as the first brick in your own model factory: a repeatable system for evaluating, improving, and deploying models you control.

​You'll see how [Union.ai](https://union.ai/?utm_source=luma) & Flyte give your AI workflows a durable runtime with infrastructure as context, so agents adapt infra resources, recover from failures, and keep moving without re-running completed work. And because it all runs in your own cloud, you own the full stack end to end: your models, your data, your infrastructure, your IP.

Related topics

AI/ML
Artificial Intelligence
Artificial Intelligence Applications
Artificial Intelligence Programming
Machine Learning

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