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LinkedIn interview questions

154 practice questions in the style of LinkedIn's interviews, covering Analytics & Experimentation, Data Manipulation (SQL/Python), Coding & Algorithms, Machine Learning, System Design, Statistics & Math, Behavioral & Leadership, ML System Design, Software Engineering Fundamentals.

Questions154

21 easy115 medium18 hard

Your progress0/154

LinkedIn interview questions by the numbers

Last updated October 28, 2026

Katkat has 154 LinkedIn interview questions. The largest topics are Coding & Algorithms (40%), System Design (19%) and Analytics & Experimentation (10%). By difficulty: 14% easy, 75% medium and 12% hard. The most common round is Onsite (49%). Frequent concepts include System Design, Algorithms, Distributed Systems and Optimization.

Topics

Difficulty

Easy14% · 21
Medium75% · 115
Hard12% · 18

Interview rounds

Onsite49% · 76
Technical Screen47% · 73
Other2% · 3
HR Screen1% · 2

Roles

Software Engineer58% · 90
Data Scientist23% · 35
Machine Learning Engineer16% · 25
DevOps Engineer2% · 3
Data Engineer1% · 1

Frequent concepts

System Design8% · 13
Algorithms8% · 12
Distributed Systems5% · 8
Optimization4% · 6
Streaming3% · 5
Arrays3% · 4

Most mentioned in interview experiences

1.Compare queueing systems and common distributions2 reports
2.Design a Distributed Key-Value Store for a Small Company's Internal Use2 reports
3.Discuss Projects and Tradeoffs2 reports
4.Explain a Difficult Technical Decision and Its Implementation2 reports
5.Explain a past project and critique a prior team2 reports
6.Explain a Project with a Diagram and Deep Dive into Your Design2 reports
7.Shortest Substring Containing Every Character of a Pattern2 reports
8.Single Queue vs Multiple Queues — Service Design2 reports
9.Analyze homepage drop and feed ranking1 report
10.Answer practical ML foundations questions1 report

Counted from 22 candidate interview experiences on Katkat. How we collect and count

Showing 151–154 of 154 results

Tight-Deadline Launch, Disagreeing With a Manager, and Guiding a Junior ScientistHard
A three-question behavioral segment from a machine learning engineer phone screen: a project launch under a tight deadline, a disagreement with your manager, and guiding a junior scientist to finish a piece of work. It tests prioritization, constructive disagreement, mentoring, and concise STAR storytelling under time pressure.
LinkedInMachine Learning EngineerBehavioral & LeadershipTechnical Screen
Transform Biased and Uniform Random Bits ExactlyMedium
Tests the ability to design and mathematically prove exact random variate generators between biased and uniform bit sources, analyzing termination and expected sample complexity.
LinkedInMachine Learning EngineerStatistics & MathTechnical Screen
Traverse a Binary Tree in Zigzag Level OrderMedium
Return binary-tree values level by level while alternating left-to-right and right-to-left order without changing level membership.
LinkedInSoftware EngineerCoding & AlgorithmsOnsite
[SQL] Job Ad Metrics with Applicant FilterMedium
This question evaluates proficiency in SQL data manipulation and deduplication, focusing on aggregations, distinct counts, and conditional filtering of event records (views vs applies).
LinkedInData ScientistData Manipulation (SQL/Python)Technical Screen

LinkedIn interview experiences

All 26 →

Debugging Logistic Regression, Then Job Click Prediction DesignLinkedIn · Machine Learning Engineer · Senior+ · Technical Screen · Oct 2026
The first part was 30 minutes of debugging a logistic regression implementation. I spent too much time on the sigmoid derivative at the start, so I didn't finish the last step, computing the gradients. Then came 20 minutes of ML design: Predict whether a member will click on a displayed job using member features, job content, and interaction history. I had to define everything myself: what data i…
Five Back-to-Back Rounds After a Layoff, Offer Within WeeksLinkedIn · Software Engineer · Onsite · Oct 2026
Offer
A layoff recently pushed me to start job hunting. A LinkedIn recruiter reached out in the second week of August. The phone screen happened the week after that. About a week later I got a call to set up the next stage, and the recruiter gave me two weeks to get ready for the full loop. They offered either a virtual or an in-person loop and I went virtual. I would have liked a gap of two or three d…
Phone Screen with Two Easy Questions, Onsite Invite a Week LaterLinkedIn · Software Engineer · Technical Screen · Oct 2026
In progress
I mass-applied to a position at the end of September, and also asked a person or two for referrals. The strange thing is that the referrals all went nowhere, and the one I applied to cold is the one that moved forward to an interview. The interviewer was pretty laid-back, maybe it's the company culture. They asked me what times I could interview, then disappeared for three or four days. Eventuall…
A Five-Round IC2 Loop With an AI/Coding RoundLinkedIn · Software Engineer · Onsite · Sep 2026
Elimination Round Maximum Depth of Binary Tree Zigzag Level Order Traversal Round 1 – DSA Max Points on a Line / Max Collinear Points Minimum Length Substring Round 2 – AI + Coding LRU Cache with Counters Given different workloads, predict and calculate the cache's hit/miss ratio. This round required combining coding with reasoning about AI/system behavior. Round 3 – Hiring Manager Behavioral int…
An Ambiguous Recommender Training TaskLinkedIn · Machine Learning Engineer · Technical Screen · Sep 2026
Rejected
This was a very strange interview experience. It was the interviewer's first time interviewing, and she asked me to handwrite a binary-classification machine learning loader and trainer. The data was not a real dataset, so I could not write code that would actually run. She asked for pseudocode but did not explain what level of detail she wanted. She also did not clarify what the model was suppos…