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LEARNING PATH · INTERMEDIATE

Software Engineer → ML Engineer

Leverage SWE skills to pivot into machine learning

A structured 9–18 month pivot leveraging your existing programming expertise. Builds math foundations, ML frameworks (scikit-learn, PyTorch), deep learning, MLOps, and a portfolio that lands ML roles.

12–18 months
10 hrs/week
2 tracks
$150,000–$210,000

TARGET ROLE

ML Engineer, Machine Learning Specialist

SALARY RANGE

$150,000–$210,000

DIFFICULTY

Intermediate

WHAT'S INCLUDED

Tracks in This Path

This path combines 2 curated learning tracks, sequenced to build on each other.

LEARNING OUTCOMES

What You'll Be Able To Do

By the end of this path, you'll have concrete, job-ready skills.

Master linear algebra, calculus, and statistics for ML

Build production ML models using scikit-learn and PyTorch

Understand deep learning architectures and when to use them

Deploy and maintain ML pipelines with MLOps principles

Create a portfolio of 3+ ML projects that showcase mastery

Land a junior or mid-level ML engineering role

FAQ

Common Questions

Do I need a math background?+
No, but you'll learn practical math for ML. Most software engineers pick it up quickly given their programming foundation.
Can I do this while working full time?+
Yes, at 10 hours per week. Many complete this in 12–18 months alongside their current job, using evenings and weekends.
What's the salary bump?+
ML engineers typically earn $30K–$60K more than backend engineers at the same level due to specialized demand.

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Ready to start this path?

Take our 2-minute quiz to confirm this is the right path for you — or dive straight in.

Last updated: 2026-03-07