Machine Learning Engineer
Visual Machine Learning Engineer learning path — phases, skills, tools, and milestones from beginner to job-ready.
Overview
The Machine Learning Engineer roadmap on Toolliyo Academy is a step-by-step visual learning path designed for developers who want clarity—not confusion. Each phase builds on the previous one with skills, tools, milestones, and links to free tutorials on Toolliyo.
Whether you are switching careers or leveling up as a ai & machine learning professional, follow this roadmap in order. Track your progress, build portfolio projects, and earn verifiable certificates as you complete Toolliyo courses and quizzes.
Visual learning path
Python & Statistics
Python for data science, statistics, probability.
- EDA notebook portfolio
Classical Machine Learning
Supervised/unsupervised learning with scikit-learn.
- Kaggle competition entry
Deep Learning
Neural networks, CNNs, RNNs, transfer learning.
- Image/NLP model deployed locally
ML Pipelines & Feature Stores
End-to-end ML pipelines, experiment tracking, reproducibility.
- Reproducible ML pipeline
Model Serving & MLOps
Deploy models with FastAPI, Docker, Kubernetes, monitoring.
- Production ML API
Scale & Optimization
Distributed training, ONNX, edge deployment.
- Optimized model benchmark
ML Engineer Career
ML system design interviews and portfolio.
- ML portfolio + system designs