ai-infra-curriculum/ai-infra-engineer-learning

AI Infrastructure Engineer Learning Track - Production ML infrastructure curriculum (2-4 years experience)

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/ 100
Emerging

This is a comprehensive learning path designed for individuals aiming to become AI Infrastructure Engineers. It provides a structured curriculum, hands-on projects, and production-grade code to teach you how to build, deploy, and maintain machine learning (ML) infrastructure at scale. The output is a highly skilled AI Infrastructure Engineer capable of developing robust and cost-optimized ML systems for large organizations.

Use this if you have 2-4 years of experience, a solid grasp of Python, Linux, Git, and ML basics, and you want to advance your career by mastering production-grade AI infrastructure and MLOps practices.

Not ideal if you are new to programming, lack foundational knowledge in Python, Linux, or basic machine learning concepts, or are looking for a quick introduction rather than a deep, career-focused learning commitment.

MLOps AI-Infrastructure Cloud-Engineering Distributed-Systems LLM-Deployment
No Package No Dependents
Maintenance 6 / 25
Adoption 8 / 25
Maturity 13 / 25
Community 17 / 25

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48

Forks

10

Language

Python

License

MIT

Last pushed

Nov 03, 2025

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