LinkedIn Coding & Algorithms Interview Questions

LinkedIn Coding & Algorithms interview questions typically focus on clean, production-minded problem solving rather than trick puzzles. Interviews evaluate algorithmic thinking, data-structure choice, complexity trade‑offs, and communication: you’ll be expected to write correct, readable code in a shared editor (CoderPad or similar), explain time/space complexity, and walk through edge cases and tests. Expect an initial 45–60 minute technical screen with one or two coding problems and a later virtual onsite with multiple rounds that probe depth, follow-up optimizations, and your ability to iterate under feedback. For effective interview preparation, practice core patterns (two pointers, sliding window, DFS/BFS, heaps, dynamic programming) and rehearse explaining your thought process aloud while coding. Time-boxed mock interviews replicate pressure and reveal gaps; review common pitfalls like off‑by‑one errors, null handling, and inefficient data structures. Emphasize clear variable names, incremental testing, and trade‑off discussion during the interview—these signal seniority and team fit as much as a correct final solution.

51 Questions 1 Company06.23.2026
Showing 20 results
Role
LinkedIn logo
LinkedIn
Medium
Software EngineerSenior+

Merge Keyed N-Ary Trees

Merge Keyed N-Ary Trees An N-ary tree node contains a unique string key among its siblings and a list of children. Implement merge_trees(a, b) for two...

Coding & Algorithms
9
0
100 people solved
Jun 11, 2026
LinkedIn logo
LinkedIn
Medium
Software Engineer Locked

Longest Run of Ones After One Flip

This question tests a candidate's ability to solve a sliding window problem involving binary arrays, extending the basic "maximum consecutive ones" pa...

Coding & Algorithms
1
0
12 people solved
Jun 23, 2026
LinkedIn logo
LinkedIn
Medium
Software Engineer

Solve common string and subarray problems

You are given three coding tasks: 1) Reverse a string - Input: a string s. - Output: the string with characters in reverse order. 2) Maximum sum of a ...

Coding & Algorithms
17
0
129 people solved
Jan 9, 2026
LinkedIn logo
LinkedIn
Medium
Machine Learning Engineer

Sample uniformly from a circle’s area

How would you generate a point (x, y) uniformly at random from the area of a circle of radius R centered at the origin? - Explain why naive choices (e...

Coding & Algorithms
17
0
127 people solved
Feb 18, 2026
LinkedIn logo
LinkedIn
Easy
Data Scientist Locked

How do you sample uniformly from an infinite stream?

This question evaluates understanding of streaming algorithms, randomized sampling and probability, and algorithmic space–time trade-offs involved in ...

Coding & Algorithms
13
0
129 people solved
Feb 1, 2026
LinkedIn logo
LinkedIn
Medium
Data Scientist

Implement stream random sampling in Python

You are given an unbounded stream of items that cannot be stored entirely in memory. Write Python code to maintain a uniform random sample from the st...

Coding & Algorithms
10
0
83 people solved
Oct 12, 2025
LinkedIn logo
LinkedIn
Medium
Data EngineerSenior+

Implement a stack supporting max and popMax

Design a data structure that behaves like a stack but also supports retrieving and removing the current maximum value. Implement a class MaxStack with...

Coding & Algorithms
9
0
78 people solved
Feb 2, 2026
LinkedIn logo
LinkedIn
Medium
Software Engineer

Group words that map to same phone digits

Problem On a classic phone keypad (T9), letters map to digits: - 2: ABC, 3: DEF, 4: GHI, 5: JKL, - 6: MNO, 7: PQRS, 8: TUV, 9: WXYZ Given a list of lo...

Coding & Algorithms
8
0
137 people solved
Oct 20, 2025
LinkedIn logo
LinkedIn
Medium
Machine Learning Engineer Locked

Implement alert queries and spike detection

This question evaluates a candidate's skills in streaming data structures, time-windowed aggregation, in-memory analytics for high-throughput alert in...

Coding & Algorithms
7
0
88 people solved
Feb 11, 2026
LinkedIn logo
LinkedIn
Medium
Software Engineer

The Celebrity Problem

The Celebrity Problem At a party there are n people, labeled 0 to n - 1. Among them there may be exactly one celebrity — a person who satisfies both o...

Coding & Algorithms
0
0
8 people solved
Jun 23, 2026
LinkedIn logo
LinkedIn
Easy
Software EngineerSenior+ Locked

Design O(1) Randomized Multiset

This question evaluates data-structure design skills, understanding of hashing and randomization for uniform sampling, handling of duplicate elements,...

Coding & Algorithms
5
0
56 people solved
Apr 6, 2026
LinkedIn logo
LinkedIn
Medium
Software Engineer

Differentiate Java final, finalize, finally

Differentiate Java's final, finalize, and finally. Define what final means for variables, methods, and classes and give examples; explain what finaliz...

Coding & Algorithms
8
0
75 people solved
Sep 6, 2025
LinkedIn logo
LinkedIn
Easy
Machine Learning Engineer Locked

Compute point-to-segment minimum distance

This question evaluates understanding of computational geometry and numerical robustness, testing the ability to compute Euclidean distances between a...

Coding & Algorithms
17
0
166 people solved
Feb 8, 2026
LinkedIn logo
LinkedIn
Medium
Software Engineer

Design a max-stack with efficient operations

Design a max-stack with efficient operations Design a stack that supports push (x), pop(), top(), peekMax(), and popMax(). The popMax operation must r...

Coding & Algorithms
8
0
71 people solved
Aug 8, 2025
LinkedIn logo
LinkedIn
Medium
Software Engineer

Merge two N-ary trees by key rules

You are given two N-ary trees A and B. Each node has: - key (string): unique among siblings (i.e., within a node’s children list, no two children shar...

Coding & Algorithms
40
0
279 people solved
Nov 21, 2025
LinkedIn logo
LinkedIn
Medium
Software Engineer

Compare heap and stack memory

Compare heap and stack memory. Explain how each is allocated and freed, typical lifetimes of data stored there, access patterns and performance charac...

Coding & Algorithms
5
0
96 people solved
Sep 6, 2025
LinkedIn logo
LinkedIn
Medium
Software Engineer Locked

Can You Place N Objects?

This question evaluates array traversal, adjacency-constraint reasoning, and greedy placement intuition, emphasizing handling of boundary conditions a...

Coding & Algorithms
8
0
71 people solved
Mar 22, 2026
LinkedIn logo
LinkedIn
Medium
Software Engineer

Find k closest values in a BST

Find k closest values in a BST Given a binary search tree with n nodes and a real target t, return k node values whose distances to t are smallest. Im...

Coding & Algorithms
5
0
101 people solved
Aug 10, 2025
LinkedIn logo
LinkedIn
Medium
Data Scientist Locked

Find index with positive suffix sums

This question evaluates array manipulation and algorithmic problem-solving skills, focusing on reasoning about cumulative (suffix) sums and time-compl...

Coding & Algorithms
4
1
97 people solved
Feb 19, 2026
LinkedIn logo
LinkedIn
Easy
Software Engineer

Count Trips From Vehicle Logs

You are given a text log of vehicle events on a road system. Each log record contains: - license_plate: a string identifying a vehicle - event_type: o...

Coding & Algorithms
2
0
20 people solved
Apr 11, 2026

Frequently Asked Questions

How difficult are LinkedIn Coding & Algorithms interview questions?
LinkedIn Coding & Algorithms interview questions typically span a range from easy to hard, but many land in the medium-to-hard category for software engineering roles. Interviewers are less interested in memorized solutions and more focused on your ability to decompose problems, reason about complexity, and deliver correct, well-tested code under time constraints. Expect algorithmic patterns like two pointers, DFS/BFS, heaps, and dynamic programming to appear, often with additional constraints that push you to optimize. If you can clearly explain tradeoffs, write clean code and handle edge cases, you’ll be well positioned even for tougher problems.
What is the typical LinkedIn interview process and where do Coding & Algorithms questions appear?
LinkedIn’s technical hiring process usually begins with a recruiter screen and then one or more technical interviews that include Coding & Algorithms challenges. These problems commonly appear in online assessments or take-home tasks used early to filter candidates, in remote technical phone or video screens where you code in a shared editor, and in onsite or final loop interviews where two focused coding rounds assess algorithmic problem solving. Depending on level, you may also face system design or behavioral interviews, but Coding & Algorithms is the throughline for most engineering roles and is evaluated at multiple stages.
How long should I prepare for LinkedIn Coding & Algorithms interviews (timeline)?
Preparation time varies by experience and current skill level, but a focused six to twelve week plan is a practical target for most candidates preparing for LinkedIn Coding & Algorithms interviews. Early weeks should refresh core data structures and algorithmic patterns, the middle weeks should emphasize solving representative problems and timed practice on shared editors, and the final weeks should focus on mock interviews, systematizing common templates, and polishing communication. If you’re already strong, three to four weeks of deliberate practice and mock interviews can suffice. Consistent, deliberate practice beats last-minute cramming.
What key subtopics within Coding & Algorithms should I prioritize for LinkedIn interviews?
Prioritize mastery of arrays and strings, pointer techniques and sliding windows, hash maps for frequency and lookup problems, and linked lists for in-place manipulations. Trees and graphs with BFS/DFS, common traversal patterns, and shortest-path reasoning are frequently tested. Dynamic programming and greedy approaches appear on more challenging problems, while heap and priority-queue use cases and union-find show up in specialized tasks. Equally important are understanding algorithmic complexity, writing correct edge-case handling for nulls and bounds, and producing readable, testable code that an interviewer can follow and discuss.
Any standout tips and common pitfalls for LinkedIn Coding & Algorithms interviews?
Start each question by asking clarifying questions and restating constraints so you and the interviewer share expectations. Sketch a clear approach before coding; if time is limited, implement a correct brute force then iterate to an optimized solution while explaining tradeoffs. Test with example inputs including edge cases and watch for off-by-one errors, null values, and overflow. Avoid over-optimizing prematurely and don’t get stuck on micro-optimizations that obscure correctness. During remote rounds, practice in the collaborative editor you’ll use and communicate continuously: silence is often interpreted as confusion, so narrate decisions and invite feedback when uncertain.

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