Meta Interview Questions

Meta Behavioral & Leadership 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.

1.2k Questions 1 Company08.08.2026
Showing 20 results
Role
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Meta
Medium
Product Manager

Hyperlink Request Flow at Facebook

End-to-End Flow: Clicking a Hyperlink in a Facebook Feature Walk through what happens end to end when a signed-in user clicks a hyperlink inside a Fac...

Product / Decision Making
14
0
46 people solved
Jul 4, 2025
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Meta
Hard
Product Manager

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...

Product / Decision Making
8
0
47 people solved
Jul 4, 2025
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Meta
Medium
Machine Learning Engineer

Discuss Research Experience and Challenges

Behavioral interview focused on prior research experience. Be prepared to describe one or two research projects you personally drove, including the pr...

Behavioral & Leadership
6
0
68 people solved
Feb 28, 2026
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Meta
Medium
Software Engineer

Describe cross-team collaboration and learning from failure

Answer the following behavioral prompts using specific examples from your experience: 1. Cross-team collaboration: Tell me about a project where you w...

Behavioral & Leadership
2
0
38 people solved
Jan 1, 2026
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Meta
Medium
Software Engineer

Describe teamwork and stress handling

Describe teamwork and stress handling This Meta Software Engineer behavioral question asks you to demonstrate, with concrete examples, how you collabo...

Behavioral & Leadership
7
0
75 people solved
Aug 7, 2025
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Meta
Medium
Software Engineer

Design a post privacy/visibility system

Design a privacy system for social media posts (similar to Facebook post privacy). Requirements: - Each post can be: Public, Friends, Friends-of-frien...

System Design
5
0
50 people solved
Feb 25, 2026
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Meta
Medium
Software Engineer

Design a price drop tracking service

Design a price tracking service like CamelCamelCamel. Requirements: - Users track products and receive alerts when price drops below a threshold. - Pe...

System Design
6
0
55 people solved
Feb 25, 2026
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Meta
Medium
Software Engineer

Design real-time live comments

Design a real-time comment system for live video (e.g., Facebook Live comments). Requirements: - Viewers post comments; all viewers see new comments q...

System Design
5
0
41 people solved
Feb 25, 2026
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Meta
Medium
Software Engineer

Design a large-scale web crawler

Design a web crawler that continuously discovers and downloads web pages. Requirements: - Start from seed URLs and crawl at scale. - Avoid duplicate c...

System Design
3
0
46 people solved
Feb 25, 2026
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Meta
Medium
Software Engineer

Design an ad click aggregation service

Design a backend service that ingests ad impression and click events and provides aggregated metrics. Requirements: - Ingest a high-volume stream of e...

System Design
3
0
44 people solved
Feb 25, 2026
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Meta
Medium
Data Scientist

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...

Statistics & Math
3
0
44 people solved
Aug 4, 2025
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Meta
Medium
Software Engineer

Find balanced subarray and increasing tree path

You are given two coding problems. Problem 1: Longest balanced subarray (0/1) Given an integer array nums of length n where each element is either 0 o...

Coding & Algorithms
6
0
64 people solved
Nov 2, 2025
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Meta
Hard
Software Engineer

Design a bank system with scheduling and rankings

Design a bank system with scheduling and rankings Design an In‑Memory Bank System (Technical Screen) You are designing an in‑memory bank ledger that s...

System Design
6
0
101 people solved
Jul 27, 2025
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Meta
Easy
Software Engineer Locked

Design a Trade Ledger Class

This question evaluates the ability to design class interfaces, choose and justify data structures for ordered storage, and reason about sorting behav...

Software Engineering Fundamentals
4
0
55 people solved
Feb 18, 2026
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Meta
Easy
Software Engineer Locked

Compute Range Sum Quickly

This question evaluates a candidate's understanding of range-sum queries, array preprocessing techniques and algorithmic complexity for answering mult...

Coding & Algorithms
3
0
49 people solved
Feb 18, 2026
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Meta
Hard
Software EngineerSenior+

Build a Mistral-powered RAG agent

Build a Minimal RAG Tool Using the Mistral API Context You have an API token and need to implement a small retrieval-augmented generation (RAG) tool i...

ML System Design
8
0
86 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Explain a recent project and measured impact

Behavioral & Leadership: High-Impact Project Deep Dive You are interviewing for a software engineering role. Provide a concise, metrics-driven walkthr...

Behavioral & Leadership
5
0
53 people solved
Sep 6, 2025
Meta logo
Meta
Medium
Software Engineer

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...

Software Engineering Fundamentals
3
0
64 people solved
Sep 6, 2025
Meta logo
Meta
Medium
Software Engineer

Clone list with random pointers

Question You are given the head of a singly linked list where each node has two pointers: next and random. The random pointer may be null or point to ...

Coding & Algorithms
3
0
47 people solved
Sep 6, 2025
Meta logo
Meta
Medium
Software Engineer

Implement merge-in-place and group cyclic-equivalent strings

You are given two ascending arrays to merge in place and a separate grouping task: Part A — In-place merge without known sizes: - Array A contains sor...

Coding & Algorithms
5
0
50 people solved
Sep 6, 2025

Frequently Asked Questions

How difficult are Meta interview questions?
Meta interview questions span a wide difficulty range because they must screen candidates from entry to senior levels across many functions. Expect coding rounds to map to medium-to-hard algorithmic problems that appear in top 100 problem lists for software engineers, and expect data roles to face challenging SQL, experiment diagnosis, and product-analytics problems that require clean metric definitions. Machine learning roles emphasize recommendation and ranking tradeoffs and model complexity, while data engineers encounter large-scale ETL and modeling puzzles. Difficulty scales with level: entry hires see clearer, bounded problems; senior hires face ambiguous tradeoffs and system-wide thinking.
What is Meta's interview process and where do these questions appear?
Meta typically runs a multi-stage process: recruiter screen, one or two technical screens or an online assessment, a full loop of onsite-style interviews, then debrief, committee review, and offer. The full loop mixes coding, system or product design, role-specific technical rounds, and behavioral interviews. Software-engineer candidates spend most time on coding and design; data scientists focus on SQL, experimentation, and product analytics; machine-learning engineers see modeling and recommendation design; data engineers handle SQL, data modeling, and pipeline questions; PMs get product-design and analytics probes. In 2025–2026 some teams pilot AI-enabled coding rounds.
How should I structure a preparation timeline for a Meta interview?
A focused six-week plan works well: weeks one and two cover fundamentals—data structures, algorithms, SQL basics, and experiment design; weeks three and four emphasize timed problem practice, mock phone screens, and role-specific cases (A/B diagnosis for data scientists, model design for MLEs, ETL modeling for data engineers); week five concentrates on system or product design and behavioral storytelling; week six is for full mock loops, timing, and refining communication. Practice with realistic tools, simulate loop pacing, and schedule a debrief after each mock to iterate on clarity, edge-case handling, and time management.
Which technical subtopics are most commonly tested for each role at Meta?
For Data Scientist interviews the recurring technical themes are product-metric definition, diagnosing experiment and spend drops, counting multi-account interactions, SQL for multi-entity metrics, and ranking or recommendation evaluation such as shop ad ranking. Software-engineer questions frequently focus on timestamped state and versioned systems, leaderboards and ranking, maze/graph traversal and tree/array transforms, delimiter and CSV parsing, and scalable search or flight-search style designs. Machine-learning engineers see place and friend recommendation design, sparse-matrix operations, ranking/loss choices, and feed dislike or personalization models. Data engineers repeatedly face entity modeling for feed and booking data, SQL analytics for utilization and reservations, and capacity-aware aggregation challenges.
What standout tips and common pitfalls should I watch for in Meta interviews?
Start interviews by clarifying requirements and expected outputs, then propose measurable success metrics; this prevents misaligned solutions. For coding, think aloud, handle edge cases, state complexity up front, and write a couple of quick tests. In design rounds quantify load, storage, and tradeoffs rather than vague features. Data roles must define metrics, guardrails, and experiment assumptions before jumping to analysis; common pitfalls are ambiguous metric definitions, peeking at tests, and ignoring instrumentation limits. For AI-assisted coding rounds, use the assistant to accelerate boilerplate but validate logic and corner cases yourself. Finish each answer with a concise summary of impact and tradeoffs.

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