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."
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"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."
Select interest thresholds under skewness and cost
Profit-Optimal Threshold Selection from an Interest Score You have a per-user interest_score s ∈ [0, 1] for a new feature. The score distribution appe...
Navigate reschedules, offers, and team-match uncertainty
Behavioral + Due Diligence + Risk Management (Data Scientist — Onsite) Context You are a Data Scientist candidate approaching an onsite. You are juggl...
Evaluate fraud classifier with cost-sensitive metrics
Binary Fraud Classifier: Metrics, Thresholding, Calibration, and Online Evaluation You inherit a binary fraud classifier used to decide whether to blo...
Derive no-click probability and sketch implications
Click Probability Across Repeated Impressions Context: We show A impressions of the same item to a user. Unless otherwise stated, each impression is a...
Evaluate shopping tab pre- and post-launch
Instagram Shopping Tab — Measuring Off‑App Purchases, Opportunity Sizing, and Launch Readout Context Instagram is planning a new Shopping tab. Users o...
Prove friends outperform unconnected; design metrics, observational analysis, and rollout experiment
Question You are given two event tables, info_stream_views (one row per viewer–post view, with viewer_id, post_id, relationship ∈ {friend, unconnected...
Compute view prevalence from views and labels
Given the tables below, write SQL to compute view prevalence of violating content. Use “today” = 2025-09-01 and report the last 7 days (2025-08-26 to ...
Solve four algorithmic problems
Solve the following coding tasks. For each, describe your approach, complexity, and handle edge cases. 1) Make parentheses string valid with minimal d...
Solve Tree Diameter and Palindromic Counts
This two-problem prompt evaluates proficiency in tree algorithms and recursion for computing longest paths in binary trees, along with string processi...
Influence Stakeholders Without Authority: Strategies and Outcomes
Influence Stakeholders Without Authority: Strategies and Outcomes Scenario Meta Data Scientist onsite behavioral & leadership loop. The interviewer pr...
Master Behavioral Interview Questions for Data/ML Roles
Master Behavioral Interview Questions for Data/ML Roles Behavioral & Leadership Interview (Data Scientist Onsite) Context You are preparing for an ons...
Explain Your Motivation for Career Transition and Role Interest
Explain Your Motivation for Career Transition and Role Interest Behavioral Phone Screen — Data Scientist Context You’re in a recruiter/technical phone...
Evaluate New Model's Performance Against Existing System
Evaluate New Model's Performance Against Existing System Scenario You are evaluating a new machine-learning model that detects harmful content on a la...
Generate unique permutations with duplicates
Given an array of integers that may contain duplicates, generate all unique permutations. Ensure no duplicate permutations are returned even if some v...
Simulate Monster Team Battles
This question evaluates a candidate's ability to model stateful simulations and implement deterministic battle mechanics with clean data structures an...
Answer conflict, ambiguity, feedback, difficult coworker prompts
Prepare behavioral answers for these prompts: 1) Describe a time you had a conflict with your manager. How did you resolve it? 2) Describe a project w...
Handle priority conflicts, setbacks, and initiatives
Behavioral Prompts Answer using a specific past experience (STAR format recommended). 1) Conflict on Priority - Tell me about a time when you and a st...
Design weapon-selling ad detection from posts
This question evaluates a candidate's ability to design a production-scale multimodal ML system for detecting weapon-selling ads, testing competencies...
Compute Bayes probability for fake accounts
This question evaluates Bayesian reasoning and probabilistic modeling skills, including conditional probability, base-rate effects, detector character...
How would you compare Facebook vs Instagram Stories?
You work on short-form ephemeral content. Both Facebook Stories and Instagram Stories exist, and leadership asks: Which product should we invest in, a...