LinkedIn Interview Questions
Practice 147 real LinkedIn interview questions for 2026. Covers all top categories — Coding & Algorithms, System Design, Analytics & Experimentation, Data Manipulation (SQL/Python), and Behavioral & Leadership — across Software Engineer, Data Scientist, Machine Learning Engineer, and Data Engineer roles. Real questions from actual interviews with detailed solutions; this collection is designed for focused interview preparation that prioritizes coding and scale-first problem solving alongside rigorous metrics thinking. Expect LinkedIn interviews to evaluate production-ready tradeoffs, clear metricization of ranking and relevance, and the ability to diagnose live-traffic regressions. For Software Engineer candidates, recurring themes include constant-time randomized data structures and frequency-weighted sampling, Top-K ranking service design and distributed-scaling considerations, plus classic array/string and stack-with-max algorithmic problems. Data Scientists should be ready for model fundamentals and optimization (logistic regression, backprop, Adam), causal and experimentation diagnostics for feed/homepage drops, and sampling/variance concerns in ranking metrics. Machine Learning Engineers will see recommendation and skills-inference system design, clustering convergence and probabilistic sampling questions, and production alerting/spike-detection. Data Engineers encounter efficient data-structure implementations tied to measurable production impact.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Resolve Simpson’s paradox in A/B email test
This question evaluates understanding of Simpson's paradox, causal inference, A/B testing and experimental design within the Analytics & Experimentati...
Explain overfitting vs underfitting and fixes
This question evaluates understanding of model generalization in supervised machine learning, focusing on the concepts of overfitting and underfitting...
How do you win project buy-in?
Answer the following behavioral questions: 1. Describe a time when you proposed a project or technical initiative and convinced your manager and other...
Sketch distributions and compare mean/median/mode
This question evaluates understanding of distributional shape, central tendency (mean, median, mode), skewness, outliers, and the effects of combining...
Design a short-video recommendation system
Design a recommendation system for a short-video feed product. Your answer should cover the full pipeline: 1. Objective and labels: Define what the sy...
Design a Skills inference system
This question evaluates the ability to design an end-to-end machine learning system for skills inference, including data source integration, labeling ...
Explain activations, losses, and Adam
This question evaluates understanding of neural network building blocks (layers and activation functions), comparative properties of activation/gating...
Derive expectation for two consecutive heads
Waiting Time Until First HH (Two Consecutive Heads) Setup Let T be the number of coin flips required until the pattern HH (two consecutive heads) appe...
Explain a past project and critique a prior team
Interview prompts 1. Project deep dive: Pick a past project you worked on and walk through it end-to-end. Be ready to use a whiteboard to explain arch...
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...
Choose better bank queue and describe distributions
This question evaluates probabilistic reasoning and statistical intuition—queueing theory for expected waiting time and variability plus distributiona...
Explain iOS ARC and avoid retain cycles
iOS Memory Management (ARC) You have 10 minutes to explain iOS memory management under ARC. Cover the following: 1. How ARC manages object lifetime (w...
Design Top K ranking system
Design Top K ranking system System Design: Real-time Top-K from a Large/Streaming Dataset Context You receive a continuous, high-volume stream of even...
Decide best email variant using stratified A/B analysis
Stratified A/B Test Across Two Strata (Week/Location) You ran an email A/B test across two strata defined by week/location. Each user receives at most...
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...
Design an in-memory key-value store using maps
Design a low-level key-value store library (like an embedded storage engine) under an interview constraint: you may use only map/dictionary-like data ...
Derive mean and variance of x̄
This question evaluates understanding of expectation, variance, covariance structure, and how dependence between observations affects the precision of...
Design LinkedIn Learning course recommendations
Design a mini ML system to recommend LinkedIn Learning courses to a user. Product goal: - Recommend courses that help the user succeed in their job se...
Handle imbalance, sampling, and overfitting
Machine Learning Fundamentals: Imbalance, Sampling, Overfitting, and Regularization You are asked several machine learning fundamentals questions in a...
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...