Meta E4 Full loop completed

I recently completed the Meta full loop interview process and am awaiting the results.

Phone screen: I answered two coding questions:

1. Binary Tree Vertical Order Traversal
2. A variation of Simplify Path

I solved both questions optimally without needing any hints. Two days later, the recruiter contacted me to schedule the full loop interviews. I requested a three-week preparation period, and they accommodated my request.

My interviews were initially scheduled over one week, but two rounds were rescheduled. All interviewers were very helpful, and despite the scheduling adjustments, it was a positive experience.

Coding Round 1: I answered two medium-difficulty questions. I solved both optimally and passed all test cases. I received a hint on one question. The interviewer commended my ability to overcome the challenging aspects of the problem.

Coding Round 2: This round consisted of one medium-difficulty question and one non- question. The first question, had a lengthy problem statement that required some time to understand. I provided a correct solution, but the interviewer guided me toward the standard approach. I eventually found the solution, and the interviewer was pleased. They acknowledged that my initial approach was also correct but that the final solution was simpler and easier to understand. The second question was a variation of the first but was not from . I coded one solution, but the interviewer did not seem satisfied. I explained a different, optimal solution but ran out of time to code it. The interviewer was happy with my explanation and stated that they don't judge solely based on coding, as my approach was what they expected.

ML System Design: This was a typical ML system design round. I explained the process from requirements gathering to deployment. I felt I performed well and answered all follow-up questions. The interviewer remained neutral throughout the interview.

Behavioral: This round went very well. I had a positive conversation about my experiences, and there were many follow-up questions.

Study Tips:

For coding, I reviewed many interview experiences and recommend practicing questions. Rank them by frequency. While Meta claims they don't ask DP questions, some problems can be solved using DP techniques, which may be expected.

For ML system design, I used Alex Xu's "Machine Learning System Design Interview" book, Educative.io's "Grokking the Machine Learning Interview" course, and Meta's "Field Guide for Machine Learning" video tutorials. This should be sufficient preparation, given prior knowledge and experience with ML projects.

For behavioral questions, preparing for Amazon's Leadership Principles was beneficial. I also studied Meta's culture and incorporated it into my responses. Always prepare different stories for different questions, using the STAR method. Practice telling your stories aloud.

Years of Experience: 4.5

I am awaiting results and am somewhat concerned about the second question in the second coding round. I will update this post once I receive the results.