MLOps Transition Plan

You've already decided you want to move into MLOps or ML Engineering. Maybe you've started learning, maybe you've even applied to a few roles. But something's not clicking, interviews feel off, your resume isn't landing, or you're just not sure if you're building the right things.

I've been exactly here. I spent years in DevOps, transitioned into ML Platform Engineering, and I'm currently navigating the ML job market. So I know what works right now, not what worked in 2021.

In 45 minutes, we'll go through your specific situation:

1. Resume review — I'll look at your actual resume and tell you how to reposition your infra background as a strength, not a gap
2. Project advice — What to build that actually shows ML capability without needing a PhD. I'll tell you what worked for me and what was a waste of weekends
3. Interview reality — The questions you'll actually face as someone coming from infra, and how to talk ML without faking it
4. Job search tactics — Where to look, how to network in, and why cold applications are mostly a black hole
5. Your personal roadmap — Based on where you are today, what should you focus on in the next 3-6 months

This isn't motivational stuff. It's a working session. We'll look at real things — your resume, your GitHub, your target roles — and make a plan.

Good fit if:

1. You've already started the transition and feel stuck
2. You're applying but not hearing back
3. You want someone to look at your actual resume and projects and give honest feedback

Not the right fit if:

1. You're just exploring whether MLOps is for you (grab the 30-min kickstart call instead)
2. You're a data scientist looking to learn ops (different problem, happy to chat separately)