Machine Learning Engineer Roadmap
You take models from notebook to production - training pipelines, serving, monitoring. Indicative 2026 salaries $95-130k US, usually reached from software engineering or data science rather than as a first job. The role is engineering-heavy: the model is 10% of the system.
By Carl Mills • Last updated • progress saves in your browser • free personalized PDF study plan.
Machine Learning Engineer roadmap FAQ
ML engineer vs AI engineer vs data scientist?
AI engineers build on hosted LLMs via APIs. ML engineers train, deploy and operate models (including fine-tuning). Data scientists analyse and prototype. ML engineering is the most infrastructure-heavy of the three and typically the hardest first job.
Do I need a GPU and deep learning to start?
No - most production ML is still tabular models (boosting) plus, increasingly, adapting foundation models. Learn the fundamentals on scikit-learn, one deep learning framework at working level, and fine-tune one small open model on a rented GPU for the experience.
What is the realistic route in?
Two doors: software engineer who takes on ML features (most common), or data scientist who owns deployment. Both take 1-2 years. A public repo that trains, serves and monitors a model end to end shortcuts a lot of gatekeeping.
What next once the list is green?
Prove it under pressure: take the free Mock Interview, then check your application signals.
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