Meta E4 Interview Experience

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ProductOngoing
November 16, 20253 reads

Summary

I recently interviewed with Meta for an E4 Product role, navigating through a phone screen and multiple onsite rounds, where I successfully tackled various coding, system design, and behavioral challenges.

Full Experience

My Meta E4 Interview Experience

I recently interviewed with Meta for their Product role at the E4 level and wanted to share my experience across the phone screen and onsite rounds.

Before the phone interview, I completed two assessments:

  • A coding assessment with 4 stages
  • A work-style assessment

Phone Screen

  1. Count number of 1s in a given subarray in a large array of 1s and 0s. I was given indices for the start and end of the subarray. I started with a simple linear approach, then optimized it to a prefix-sum solution: prefix[end] - prefix[start - 1]. Follow-ups included questions on handling digits 0–9 instead of binary, and how to handle cases like start > end.
  2. Find Lowest Common Ancestor of a Binary Tree. I implemented the standard recursive LCA algorithm and walked through examples. I missed one edge case where p and q have the same value, and needed a small hint for the scenario where both references point to the same node.

Overall Phone Screen Feedback was positive: strong coding, clear communication, and fast implementation. Improvements were suggested in clarifying questions and edge-case coverage.

Onsite Rounds

Round 1

  1. Find first 1 in a sorted binary matrix. I solved this problem cleanly.
  2. Trapping Rain Water. I solved this problem cleanly.

Round 2 (Design Round)

I was asked to design a concert ticket booking service for a small scale (one venue, many concerts). I discussed requirements, user flows, API design, data model, and bottlenecks. I drove the conversation end-to-end, providing detailed but clear explanations, and moved quickly through the design choices. I also pushed back when needed to clarify assumptions.

Round 3

  1. Valid Palindrome II.
  2. Valid Word Abbreviation.

I solved both of these problems without any issues.

Round 4 (Behavioral)

This was a standard behavioral round with questions focused on handling ambiguity, conflict resolution, and using data to drive decisions. It was a straightforward conversation centered around my past experiences, demonstrating ownership, and highlighting collaborative efforts.

Interview Questions (8)

Q1
Count Ones in Subarray
Data Structures & AlgorithmsMedium

Given a large array of 1s and 0s, and indices for the start and end of a subarray, count the number of 1s within that subarray. Follow-ups included handling digits 0-9 instead of binary, and cases like start > end.

Q2
Lowest Common Ancestor of a Binary Tree
Data Structures & AlgorithmsMedium

Find the Lowest Common Ancestor (LCA) of two given nodes in a binary tree.

Q3
Find First One in Sorted Binary Matrix
Data Structures & AlgorithmsMedium

Find the position of the first '1' in a matrix where each row is sorted and contains only 0s and 1s.

Q4
Trapping Rain Water
Data Structures & AlgorithmsHard

Given n non-negative integers representing an elevation map where the width of each bar is 1, compute how much water it can trap after raining.

Q5
Design a Concert Ticket Booking Service
System DesignHard

Design a concert ticket booking service, specifically for a small scale scenario with one venue and multiple concerts. The discussion covered requirements, user flows, API design, data modeling, and identifying bottlenecks.

Q6
Valid Palindrome II
Data Structures & AlgorithmsEasy

Given a string s, return true if the s can be palindrome after deleting at most one character from it.

Q7
Valid Word Abbreviation
Data Structures & AlgorithmsMedium

Given a word and an abbreviation, check if the word matches the abbreviation. For example, 'internationalization' can be abbreviated as 'i12n' or 'i5s4n'.

Q8
Behavioral Interview
Behavioral

This round involved standard behavioral questions, with a focus on topics such as handling ambiguity, resolving conflicts, and using data to inform decisions. The conversation revolved around past experiences, ownership, and collaboration.

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