Having the required skillset for passing technical interviews at big companies like Meta, Apple, Amazon, Netflix, and Google (MAANG companies), as well as with advanced quantitative firms is rather simple, and all you need to master is just one skillset – acing the interview loop. Technical interview process with major tech companies in the United States of America includes solving problems with Data Structures and Algorithms (DSA) and System Design.

The thing is that major tech companies expect you not to demonstrate your trivia knowledge and API calls of a certain programming language, but to solve some hard algorithmic problems using pattern recognition, memory allocation knowledge, and engineering trade-offs under pressure. Below you will find problem categories that are asked by major tech companies in the USA and are classified by types of problem solving.

1. Meta: Fast-Paced Pattern Recognition

Meta is famous for its fast-paced technical interview process. At Meta interview loop, Meta expects you to solve two different algorithmic problems in 45 minutes. With such a tight timeframe, Meta expects you to have good pattern recognition abilities, outstanding communication skills, and efficient implementation of common algorithms.

Questions They Love to Ask

Subarray Sum Equals K: Given an integer array and an integer k, return the total number of subarrays whose sum equals k.

Pattern: Hash Map Optimization. In naive approach using nested loops results in inefficient O(N^2) performance. To solve this problem, you should be able to implement prefix sum tracking and Hash Map that gives O(N) performance.

K Closest Points to Origin: Given a list of points (x, y) in a two-dimensional space, return the k closest points to the absolute origin point (0, 0).

Pattern: Heap/Priority Queue. This question checks your ability to work with perfectly sorted subsets of data. Max-Heap allows doing that with dynamic constant-time operations.

2. Google: Ambiguity and Infinite Edge Cases

Unlike Meta, Google expects you to solve an ambiguous and open-ended problem. As soon as you start explaining your approach, Google interviewers will shift goalposts by introducing additional constraints, scaling input size, and infinite edge cases.

Questions They Love to Ask

Longest Increasing Path in a Matrix: Given an integer matrix, find the length of the longest increasing path in it. You can move only horizontally or vertically, but cannot step on numbers smaller than the current number or exceed matrix bounds.

Pattern: Graph Traversal with Dynamic Programming. This problem checks your DFS and DP skills. To avoid exponential recursion, apply memoization.

Find Median from Data Stream: Design a structure that receives a continuous stream of numbers from the network and calculates the median of all numbers in real-time.

Pattern: Dual Heaps. To design a solution, you need to know how to implement Max-Heap (smallest half) and Min-Heap (largest half) to calculate median in constant time.

3. Amazon: Scalability and Logistics

Amazon is obsessed with scalability and resource optimization. All Amazon coding problems are designed to emulate real-life situations that may occur when building large e-commerce infrastructure or logistics network.

Questions They Love to Ask

LRU Cache (Least Recently Used): Develop Least Recently Used cache data structure that provides constant-time lookup and insertion operations.

Pattern: Combined Data Structures. To implement constant-time performance, you need to combine Hash Table (instant lookup) and Doubly-Linked List (memory rewrite and priority adjustment of cache nodes).

Number of Islands: You are given a two-dimensional grid consisting of 1s (land) and 0s (water). Count the number of separate islands in this grid.

Pattern: Graph Traversal (BFS/DFS). Traverse the grid using BFS/DFS treating adjacent land cells as graph nodes and flooding land area till water boundaries.

4. Netflix: Optimizations and Streaming Logic

Netflix looks for engineers who can operate independently, make architecture decisions, and optimize data delivery pipeline. Netflix interview questions are usually related to recommendation algorithms, sessions tracking, and microservices streams orchestration.

Questions They Love to Ask

Merge Intervals: You are given a list of overlapping time intervals (video streams or server access logs). Merge all overlapping intervals and return the resulting array.

Pattern: Array Sorting and Greedy Algorithm. First, you need to sort custom objects by their starting points and then iteratively merge the active interval cache.

Top K Frequent Elements: Given an array of integers, return the k most frequent elements.

Pattern: Hash Table Frequency Counting and Min-Heap Filtering. To solve this problem, you need to use Hash Table map to calculate frequencies of array elements and filter top k elements with Min-Heap without sorting.

5. Apple: Low-Level Memory and Hardware Management

Engineering track at Apple is all about data integrity and system resources management. Backend and systems coding interviews at Apple include string manipulation, bitwise operations, and memory optimizations.

Questions They Love to Ask

Product of Array Except Self: You are given an array of integers. Write a function that returns a new array where each element is the product of all other elements except itself. The task here is not to use division operation.

Pattern: Prefix and Suffix Arrays. Apple expects you to develop a solution avoiding nested loops and running in O(N) linear time. It often requires to optimize space complexity to O(1).

Validate Binary Search Tree: You are given a root node of a binary tree. Determine whether the tree is a valid binary search tree.

Pattern: Tree Traversal and Range Validation. This problem checks your recursion skills. You need to pass the math range minimum and maximum values through recursive calls and validate whether nested left and right children meet BST requirements.