Cracking Meta's ML Design Interview: Insights on Recommendation Systems Challenges

meta | | Interview Experience

Interview Date: Not specified
Result: Not specified
Difficulty: Not specified

Interview Process

The interview lasted 45 minutes and focused on machine learning design, specifically on a Yelp-like place recommendation system. The discussion did not cover search ranking but went directly to personalized discovery. The interviewer delved into feature engineering in detail and encouraged the candidate to discuss the pros and cons of the modeling approach.

Technical Questions

  1. Recommendation Systems

Tips & Insights

It is beneficial to be prepared for in-depth discussions on feature engineering and to proactively address the advantages and disadvantages of your modeling choices.