Google | SWE L4 | NYC | September 2020 [Reject]
Summary
I interviewed for a Software Engineer L4 position at Google in NYC in September 2020. Despite a rigorous interview process involving a phone screen and a five-round virtual onsite, I ultimately received a rejection.
Full Experience
My interview journey for the Google SWE L4 role started with a phone screen, which involved a coding problem. Following that, I was invited for a virtual onsite, consisting of five 45-minute rounds. These rounds covered a mix of coding challenges, a behavioral interview focusing on 'Googliness,' and other algorithmic problems. Each coding round presented unique challenges, from dynamic programming to graph-related problems. Unfortunately, after completing all rounds, I was informed that I would not be moving forward with the hiring process.
Interview Questions (6)
Contains Duplicate II
Given an integer array nums and an integer k, return true if there are two distinct indices i and j in the array such that nums[i] == nums[j] and abs(i - j) <= k.
Blackjack Probability of Busting
Given a 10-sided die (d10) and a starting value, what is the probability of busting (getting over 21) under specific rules: if the current sum is 16 or lower, one must roll; if the sum is 17-21, one must stay.
Minimum Window Subsequence
Given two strings S and T, return the minimum window in S which has T as a subsequence. If there is no such window, return the empty string.
Anagram Pair and Smallest Non-Anagram Number
The round consisted of two parts. Part 1: Determine if two given numbers are anagrams of each other. Part 2: Given a list of numbers, find the smallest number from the list that does not have an anagram pair within the same list.
Googliness Behavioral Interview
This round focused on behavioral questions, often referred to as 'Googliness', assessing leadership, teamwork, handling ambiguity, and how I demonstrate Google's core values.
Maximize Minimum Distance Path in Grid
Given a 2D grid containing a starting position, an ending position, and several obstacles, find a path from the source to the destination such that the minimum distance maintained from any obstacle along this path is maximized.