Machine Learning Interview at places like FAANG

[Cisc0]

Imagine you've got a machine learning interview lined up with one of the big players like FAANG or something in that league, you've got a few weeks to prep, and you want to make the most of it. Where do you focus your energy?
The kind of prep that goes beyond daily Leetcode, stuff like getting really solid on ML system design, revisiting the fundamentals in a way that actually sticks, being able to talk through modeling tradeoffs clearly, and tackling those ambiguous product style ML questions that test more than just technical skill. Trust me I talk like I've been in one cos I have not just for the big leagues, probably want to brush up on theory, but also be able to talk shop on real world applications those and those "what would you do if..." type of questions that can go in any direction.
Who else can relate? and what's your experience

 

[abcdefu]

@Cisc0 You're right on the money with system design and tradeoffs. Also try and maybe dig into past projects so you can explain your decision-making like you're walking a PM through it.

 

[DandD]

When you were prepping, did you find it more valuable to deep dive into theory and algorithms, or to focus on building and explaining real-world ML systems that demonstrate you can handle messy, ambiguous problems under pressure?

 

[flappybird]

I'd suggest you focus on nailing the fundamentals, getting sharp on system design and practicing how to explain tradeoffs and tackle open-ended "what would you do if…" questions. Leetcode helps, but what really matters is showing you can think clearly about messy, real world problems and connect models to impact.