DevOps → MLOps

So you're in DevOps or infrastructure, and you want to break into MLOps or ML Platform Engineering. Cool. But every roadmap on the internet is either made by someone who's never done it, or it's a 47-step checklist that makes you want to quit before you start.

I made this transition myself, from years of pure DevOps to ML Platform Engineering, where I manage 100+ clusters and 100+ GPUs in production. I know what actually helped and what was a complete waste of time.

This is a quick 30-minute call where I'll give you a clear picture of the path.

We'll talk about:

1. What MLOps actually is in practice (not the Medium article version)
2. Which ML foundations you genuinely need vs what you can learn on the job
3. The skills from your DevOps/SWE background that are already gold, and how to see them that way
4. Certifications, which ones matter, which ones don't
5. Common mistakes people make in this transition and how to dodge them
6. A rough learning order so you're not jumping between 15 Udemy courses

Think of this as an honest conversation with someone slightly ahead of you on the same road. No fluff, no upselling, just straight talk.

Good fit if:

1. You're early in exploring this transition
2. You want clarity before committing months to learning
3. You're confused by conflicting advice online