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Machine learning engineers are earning $250K+… and the fastest path to becoming one has completely changed.
I’ve worked closely with ML engineers across top tech companies and watched the industry shift in real time from classic machine learning to GenAI, LLMs, and full-stack AI deployment.
If you’re still following old roadmaps that tell you to spend months on theory before building anything… you’re already behind.
This video gives you the exact modern roadmap to become a Machine Learning Engineer in 2026 focused on real skills, real projects, and what hiring managers actually want.
🚀 What you’ll learn
✅ What’s changed in ML careers (and why old roadmaps don’t work anymore)
✅ The fastest way to build strong Python + data foundations
✅ Core machine learning skills every engineer must master
✅ Deep learning, transformers, and large language models explained simply
✅ How to build real-world GenAI and RAG applications
✅ MLOps, deployment, and production-ready AI systems
✅ The T-shaped skill strategy top ML engineers use
✅ Real portfolio projects that actually get you hired
Timestamps
0:00 ML Job Market
0:55 Role of ML Engg. Has Changed
1:56 Phase 1
3:05 Phase 2
5:09 Phase 3
6:32 Phase 4
7:36 ML Projects
about me
I’m Maddy, a senior software engineer (prev. at Google), with prior internships at Microsoft, Morgan Stanley, IBM, and Amazon. Sharing my journey here - thanks for watching 🤍
🔗find me on other socials
Instagram / madeline.m.zhang
LinkedIn / madelinemzhang
Tiktok / madeline.m.zhang
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*disclaimer: views are all my own and do not represent any current / past employer(s)
Thank you to Coursera for sponsoring this video
Some of the links in the description are affiliate links, which may earn me a commission if you make a purchase, without any added cost to you.
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