A hands-on learning journey to become a Model Inference / AI Infrastructure Engineer by 2027.
Hey there!
I am a software engineer with a background in Python, C#, Ruby and a bunch of other languages. My main focus has been on backend development, cloud infrastructure, and DevOps practices for the past 15+ years. I have lead teams in building scalable systems at various startups and enterprises in Russia and Europe.
I have a keen interest in AI, deep learning and its applications, and I want to specialize in inference engineering to work on the infrastructure that powers AI models.
I started exploring ML back in 2018 out of curiosity, but I didn't have the time to dive deep. In 2019, I took a course from Yandex Practicum on Data Science, but didn't finish it. Even though I didn't complete the course, I learned some foundational concepts about data analysis and machine learning.
A couple of years later, I joined statice.ai as a software engineer, where I worked on building a data anonymization platform. This experience reignited my interest in AI and ML, particularly in the context of ML infrastructure. While working at statice.ai closely with Data Scientists and ML Engineers, I realized that optimizing model inference, creating efficient pipelines, and ensuring robust deployment processes are crucial for the success of AI applications. And that's what I enjoy the most. I'm an Engineer at heart.
After leaving statice.ai, I joined planfact.io as a CTO, where I continued helping the company build foundation for their next 10 years of growth. However, I still felt the pull towards inference engineering and AI infrastructure. I want to focus on the technical challenges of building and maintaining the systems that enable AI models to perform at scale.
So, with all the support of ChatGPT, I created my own personalized learning plan to become an Inference Engineer. This repository is a record of my journey, including the resources I use and the projects I work on. I hope it will be helpful for others who want to follow a similar path.
- Start: August 1, 2025
- Goal: Inference Engineer by mid-2027
I plan my learning in weekly sprints, focusing on different aspects of inference engineering. Each week has specific goals and daily tasks. To see how each week is structured, check out the weekly_planning directory.
I maintain a daily journal to track my progress, challenges, and learnings. You can find my daily entries in the daily_journal directory.
I do keep Jupyter notebooks for hands-on learning, especially with fastbook. You can find them in the projects_and_experiments directory.
To reproduce my environment, see environment.md
P.S. I use Obsidian as a primary note-taking tool around my learnings. This is why the structure is a bit different from a typical GitHub repository. The directories are organized to fit my workflow in Obsidian. You can even use templates from the templates along with Templater plugin to create your own notes. If you find broken links or missing files, please let me know by opening an issue.
Andrey Krisanov, 2025