In this series of Machine Learning Infrastructure Interview, I will share my journey of learning and pursuing Machine Learning Infrastructure as a career path from the beginning to the Senior level.

Machine Learning Infrastructure is a part of a Machine Learning System. Machine Learning System is still a developing area, and it's very potential. There are many opportunities and challenges when building a Machine Learning System that people are trying to solve. However, in this Machine Learning Infrastructure Interview series, we will not discuss what a Machine Learning System is or what challenges Machine Learning Systems face. For those topics, please refer to my other series The Ultimate Machine Learning System.

This Machine Learning Infrastructure Interview series focuses more on the interview process and interview questions of the Machine Learning Infrastructure, Machine Learning Platform, and MLOps roles. For the definition of the Machine Learning Infrastructure engineer and Machine Learning Platform engineer, please refer to this Machine Learning Interviews Book (opens in a new tab). For the Machine Learning System Interview, I recommend you to read these resources Designing Machine Learning Systems (opens in a new tab) and CS 329S - Machine Learning Systems Design (opens in a new tab). To differentiate Machine Learning System, Machine Learning Infrastructure, and Machine Learning Platform, please refer to this post Deployment - ML Infrastructure.

Generally, after going through this Machine Learning Infrastructure Interview series, you will have an overview of what knowledge you might need to learn, what tools and technologies you might need to know, which topics you should practice for the Machine Learning Infrastructure Interview, what tips and tricks you might need in order to increase the chance of being offered, and the most important thing, how the real Machine Learning Infrastructure Interview questions look like.

I'll see you in the next post, my Machine Learning Infrastructure Roadmap.