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."
Extend a Maze Solver
This question evaluates competence in graph search and state-space modeling, specifically BFS-based pathfinding, constrained traversal rules (directio...
Discuss conflicts, proudest project, and departure reasons
Behavioral & Leadership Questions — Machine Learning Engineer (Technical Screen) Answer the following prompts concisely, using concrete examples from ...
How would you measure Group Call success?
You are interviewing for a Data Scientist role at a social communication product similar to Meta. The team asks you to evaluate a Group Call feature t...
Construct a 95% Confidence Interval for Comment Counts
Construct a 95% Confidence Interval for Comment Counts Comment Activity Analysis: Mean CI, Sampling Distribution, and 95th Percentile Context You have...
Evaluate Product-Ranking Algorithm with Precision and Recall Metrics
Evaluate Product-Ranking Algorithm with Precision and Recall Metrics Scenario Instagram Shopping wants to improve its product‑ranking algorithm for th...
How to decide if users need a new feature
You are a Data Scientist at a social app. The product team proposes a new in-app feature (e.g., a new sharing surface). You have event-level data and ...
Solve matrix diagonal and sliding-window statistics
Solve matrix diagonal and sliding-window statistics 1) Given an m x n integer matrix, determine whether every top-left to bottom-right diagonal has th...
Design leaderboard and messenger systems
Design leaderboard and messenger systems This Meta onsite system-design round asks you to design two large-scale systems back to back. Cover end-to-en...
Compute Range Sum Quickly
This question evaluates a candidate's understanding of range-sum queries, array preprocessing techniques and algorithmic complexity for answering mult...
Design LRU cache and pick k closest points
Design LRU cache and pick k closest points 1) Design a fixed-capacity in-memory cache that evicts the least recently used key when full. Support get(k...
Investigate why an advertiser’s spend decreased
This question evaluates a Data Scientist's competency in analytics and experimentation—specifically root-cause analysis of ad spend declines, attribut...
Handle diverse styles and give constructive feedback
Behavioral: Collaboration, diversity, feedback, documentation Answer the following using specific examples from your past experience. 1. Diversity & i...
Design a recommendation system
System Design: Large-Scale Home-Feed Recommendation System Problem Design a large-scale recommendation system for a consumer app's home feed. Describe...
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...
Design a basic bank system API
In-Memory Bank System: API, Data Model, Invariants, Semantics, and Edge Cases Goal Design and implement an in-memory bank system that supports account...
Define and analyze product metrics
Product Analytics Case: Short‑Form Video Feed Context: You are evaluating a short‑form video feed feature inside a large social app where users swipe ...
Design unit tests for grid navigation
Mouse-Maze Controller: Design a Comprehensive Unit Test Suite Context (assumptions to make the task self-contained) Assume we are testing a controller...
Solve four data structure and algorithms tasks
1) Print the numbers at each level of a binary tree. Given the root, output the values level-by-level (each level on a new line or as a list of lists)...
Walk through resume and plan team success
Behavioral/Leadership Prompt — Technical Screen (Software Engineer) You are interviewing for a Software Engineer role in a technical screen focused on...
Design an Instagram-like photo-sharing platform
System Design: Instagram-like Photo and Short-Video Platform Goal Design an Instagram-like platform for photos and short videos. The design should cov...