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."
Analyze ad targeting expectations and distributions
Ads Profit, Variance Decomposition, and Exponential Timing Context: You run an ad slot with two user segments. On each eligible page view (impression ...
Compare first-score vs all-scores estimators
This question evaluates statistical estimation and inference competencies—specifically understanding estimator definitions, weighting and sampling eff...
Choose KPIs for short-video recommendations
This question evaluates a data scientist's ability to define precise product metrics, set guardrails, design and power A/B tests, and apply weighted d...
Set the Group Call participant cap
We must set a maximum participants cap K for Group Calls. You have telemetry at the call level: calls(call_id, start_ts, participants_count, video_on_...
Decide event notification launch via experiments
This question evaluates a data scientist's competency in experimentation design, causal inference under network interference, metric engineering, and ...
Choose ML metrics under asymmetric costs
This question evaluates a data scientist's competency in cost-sensitive binary classification, covering skills such as defining business cost matrices...
Quantify base-rate dilution in CTR
Weighted-Average CTR and Volume Requirements You are assessing the impact of introducing a new high-CTR event notification into an existing stream of ...
Brainstorm how to optimize email engagement
Lifecycle Email: Increase Incremental On‑Site Engagement You own lifecycle email for a large consumer app and are tasked with increasing on‑site engag...
Design experiment with network and novelty effects
This question evaluates a data scientist's competence in experimental design and causal inference under network interference and novelty effects, cove...
Choose metrics for fake-user classifier
Classifying Fake Accounts: Metrics, Capacity, Thresholding, and Validation Context - Population: 10,000,000 daily active users (DAU) - True fake rate ...
Design an A/B test for comments UI
This question evaluates experimental design, causal inference, statistical power calculation, variance-reduction techniques, sequential monitoring, an...
Compute and correct correlation significance inflation
This question evaluates statistical inference for correlations, multiple testing control (false discovery rate), power and sample-size calculations, a...
Estimate fake-account prevalence with capture-recapture
This question evaluates a data scientist's competency in capture–recapture estimation, estimation of population size with incomplete detections, stati...
Google–Roomba Acquisition Strategy
Acquisition Strategy Case: Should Google Acquire iRobot and Roomba? Assume you are evaluating a hypothetical acquisition of iRobot, the maker of Roomb...
Posts and Replies Engagement
Posts and Replies Engagement A content platform stores user-generated posts and the replies that those posts receive. You need to answer two questions...
Compute Sliding Window Averages
This question evaluates proficiency in array manipulation, sliding-window techniques, and algorithmic efficiency including time and space complexity. ...
Write Call Analytics SQL Queries
This question evaluates SQL data manipulation and analytical competencies, including aggregation, joins between user and event tables, time-window fil...
Solve four OA coding problems
This set of four problems evaluates core algorithmic competencies including array manipulation and counting in sorted arrays, resource-constrained opt...
Implement BST Iterator and Ticket Queue
This question evaluates understanding of binary search tree traversal and iterator design with amortized time and space analysis, as well as dynamic p...
Deep copy a linked list with random pointers
This question evaluates understanding of linked-list structures, pointer/reference manipulation, deep versus shallow copying, and the ability to analy...