LinkedIn Machine Learning Engineer Interview Questions
Practice the exact questions companies are asking right now.
"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."
Answer practical ML foundations questions
In an ML interview, you are asked a series of practical ML foundation questions: 1) Model outputs probabilities. When do you need probability calibrat...
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...
Plan and lead a large recommendation project
You are given a recommendation design problem, but the interviewer focuses on leadership and execution rather than detailed modeling. Explain how you ...
Explain activations, losses, and Adam
This question evaluates understanding of neural network building blocks (layers and activation functions), comparative properties of activation/gating...
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...
Design a distributed key-value store
Design a distributed key-value store Design a Distributed Key–Value Store (Technical Screen) Context You're designing a cloud-native, multi-tenant key...
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...
Design a system for LinkedIn Skills
Design an ML system for “LinkedIn Skills”. The system should infer and/or recommend skills for members, and support downstream use cases like search/r...
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...
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...
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 ...
Design a scalable metrics monitoring system
Design a scalable metrics monitoring system Design a Metrics Monitoring System for Large-Scale Services Context You are designing a metrics monitoring...
Explain Core ML Fundamentals
Review ML fundamentals including logistic regression, cross-entropy loss, batch versus stochastic gradient descent, batch size tradeoffs, overfitting,...
Implement K-Means and Explain Convergence
Implement K-means clustering in Python and explain convergence. Covers assignment and update steps, stopping criteria, empty clusters, objective funct...
Generate uniform 0–6 from biased coin
You are given a function: - int getRandom01Biased() returns 0 with probability p and 1 with probability 1-p, where p is unknown and may be any value i...
Find shortest word transformation with caching
Find shortest word transformation with caching You are given a start word and an end word of equal length, and a dictionary of valid words. In one mov...
Compute total covered interval length
Compute total covered interval length Given a list of integer intervals [l, r) (half-open), compute the total length covered by at least one interval....
Sample index from weighted probability distribution
Given an array weights[0..M-1] representing a discrete distribution over M outcomes, implement a function sampleIndex(weights) that returns an index i...
Sample index from probability distribution
This question evaluates proficiency in randomized algorithms and probability-based sampling, along with algorithmic preprocessing and data-structure d...