Meta Interview Questions
Practice 1,159 real Meta interview questions for 2026. Covers top categories — Coding & Algorithms, Analytics & Experimentation, Data Manipulation (SQL/Python), Behavioral & Leadership, and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Data Engineer, and Product Manager roles. Real questions from actual interviews with detailed solutions. Expect a software-engineering-heavy loop: timed algorithmic coding (trees, arrays, graph/maze problems, delimiter/CSV parsing), system-design prompts like leaderboards, flight search and online-judge architectures, and an increasingly common AI-assisted coding round that mirrors real workflows. Data Scientist rounds emphasize product analytics and experimentation—designing tests, diagnosing spend drops and bots, evaluating unconnected content, and writing SQL for multi-account, seller, and vehicle metrics. Machine Learning Engineer questions skew toward recommender and ranking work (place and friend recommendation, sparse-matrix ops, linear-regression derivations, newsfeed dislike models). Data Engineers focus on data modeling, ETL, capacity calculations, reservations/utilization queries, and production SQL/Python tasks. For interview preparation, prioritize timed coding practice, system-design templates, rigorous SQL drills (joins/CTEs/aggregation), clear A/B-testing frameworks, and concise STAR behavioral stories tied to measurable 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."
Detect cycles and order with DFS
You are given a directed graph of package dependencies represented as an adjacency list: Map<String, List<String>> deps where deps[p] lists packages t...
Remove minimum parentheses to balance string
Given a string s containing lowercase letters and the characters '(' and ')', remove the minimum number of parentheses so that the resulting string is...
Solve common array/string/linked-list tasks
You may be asked one or more of the following independent coding tasks. For each task, implement an efficient algorithm and clearly state time/space c...
Design structure for top-K frequent elements
You are working with a large collection of items represented by integer IDs (e.g., product IDs, user IDs, etc.). Updates and queries arrive over time....
Design ticketing and coding practice platforms
You are asked two separate system design questions. --- 1. Design an online event ticketing platform (like Ticketmaster) Design a large-scale web serv...
Determine Superiority of Model A Using Hypothesis Testing
Hypothesis Test: Is Model A Better Than Model B? A search feature marks a session as successful only when both relevancy and accuracy binary flags equ...
Evaluate Impact of Targeting Ads to High-Intent Users
Evaluate Impact of Targeting Ads to High-Intent Users A product manager proposes allocating all ad impressions to users predicted to be high intent, a...
Calculate Expected Day for First Selection in Sampling
Expected Day of First Selection in Daily Sampling There are 1,000 people. Each day, 10 distinct names are selected uniformly at random. Day counting s...
Determine Probability of Shared Videos in Recommendations
Meta statistics and product prompt on video recommendation overlap, covering combinations, probability of shared videos, expected intersection size, s...
Evaluate Instagram's Short-Video Recommender System Success
Evaluate Instagram's Short-Video Recommender System Success Instagram is launching a short-video recommender feed. You are asked to choose metrics, re...
Fake Accounts [AE]
Evaluates probability, classification metrics, and feature engineering for fake-account detection. Strong answers apply Bayes' rule with rate-weighted...
Describe Handling Unexpected Changes and Data-Driven Conflicts
Describe Handling Unexpected Changes and Data-Driven Conflicts This behavioral interview prompt assesses cultural fit, ownership, communication, adapt...
How would you evaluate upranking Shop ads?
Meta is considering upranking ads that send users to an in-app Shop experience (for example, Facebook/Instagram Shops) relative to ads that send users...
Analyze Multiple-Account Users in SQL
This question evaluates a data scientist's ability to perform SQL-level user- and account-level aggregation, grouping, and NULL-aware filtering to com...
Design recommendation and weapon-ad detection systems
This question evaluates proficiency in end-to-end ML system design, covering scalable recommendation systems and safety-focused ad classification with...
Build Friend Recommendations
This question evaluates proficiency with graph data structures, set operations, uniform random sampling, counting mutual connections, and deterministi...
Size opportunity for new product line
An e-commerce site considers adding a "Home Office" product line. Before any A/B test, size the opportunity and recommend whether to proceed. Assumpti...
Design and critique teen-parent impact experiment
Causal Impact of Parental Registration on Teen Outcomes Meta plans to let parents register and link to their teen’s account. Leaders are concerned abo...
Run a clean A/B test for recommendations
You must run an A/B test to evaluate the new hashtag recommender starting on 2025‑09‑01. 1) Define the randomization unit (user/session/impression) an...
Estimate variance for ratio metrics
KPI Variance via Delta Method and Inference Choices for ARPU Context You run experiments where each arm produces aggregate totals per analysis unit (e...