GoKawiilMy Google Recruitment Journey (Part 1): Brute-Forcing My Algorithmic Ignorance
Introduction
About 2 months ago, an email from xwf.google.com dropped into my inbox, referencing an application from a year prior that I even forgot about. My initial classification was that it is not possible and that this is just spam. But after the screening call, the reality hit: I will have two online interviews (one technical, one behavioral) in just a week. And not just a regular interview to another company, these will be interviews for a company that I still consider as one of the top-of-the-world factory of engineers.
This was a critical state. I’ve worked as a software developer in telecommunications for a few years, focusing on high-level abstraction: routing, message processing, and writing business logic. In my hobbyist gamedev projects, even though sometimes I liked to make some pathfinding algorithm or to do a CPU 3D rasterizer by hand, at the end of the day my metric for success was simple: if it runs at >60 FPS without drops, it ships.
My data structures were pragmatic: flat vectors, statically sized arrays, sometimes simple maps, and for hard problems "SQLite". And all of my attempt at writing fancy algorithms or data structure was a cool learning journey, that unfortunately did not have a direct impact on my job skills, and there were always better ways to spend this time if I wanted to optimize for a telecommunications career as well as for a gamedev career.
Classical algorithms and strict LeetCode-style data structures were always outside my area of interest. My earliest attempts at learning them had failed completely. Even in my earliest memories on all primary school programming contests, I always failed at them.
I had one week, a day job, other regular obligations and a fundamental knowledge gap.
Day 0: Making the plan and procrastination dressed as learning.
After some initial thinking (I mean procrastination on YouTube and online forums for at least a few hours for few days), I realized that the most successful strategy would be to learn as many patterns as possible - to at least be able to identify the core problems. I was aware that I had a very small chance of resolving it in the most optimal way during the interview, so I wanted to at least understand what was expected from me to do (for my brain that is trained on writing software and resolving useful problems, mathematical description is not clear in a lot of places, and for me, it hides the clue, especially behind artificially created, non-real problems).
I knew that if I start reading an algorithm book, I would fail because I didn't have time to deal with concepts obscured by pure math.
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