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Meta Interview Guide

Meta's coding interviews are fast, standardized, and — since 2025 — partly AI-assisted. Two problems in 40 minutes, no DP, hints encouraged, bugs tolerated. This guide covers every round, what actually gets tested, and the insider details that change how you prep.

30% easy, 55% medium, 15% hard|15 tracked problems|4–8 week timeline

What makes Meta different

Meta's coding loop is the speed interview of Big Tech. Forty minutes. Two problems. Both need to be talked through. interviewing.io and Exponent both describe the same shape across Meta writeups: Google gives 45 minutes for one problem with silence time, Meta doubles the question density and watches how fast you move. The real question here is whether you can make good decisions under pressure, not whether you can admire the problem for a while.

The other thing that is genuinely unique: Meta banned dynamic programming from coding rounds. Completely. This trips up candidates who spend weeks grinding DP because it works elsewhere — interviewing.io's Meta guide explicitly flags the DP-grind trap. At Meta, that prep does not transfer. Redirect that energy to arrays, trees, graphs, and hash tables. Those four categories cover roughly 80% of what Meta asks.

Since late 2025, one onsite coding round has been AI-assisted: you get a full IDE with a model chooser dropdown, with Llama 4 as the default and GPT-4o mini, Claude, or Gemini as alternatives. That rollout is expanding across SWE roles through 2026. The AI-assisted round is closer to real production work than a whiteboard — which also means the failure mode is predictable: accepting AI output too quickly. The strong answer names the trade-off, checks the suggestion, and treats the model like a fast intern, not an oracle.

The interview itself is more collaborative than most candidates expect. Meta trains interviewers to give good hints, and that training matters enough that hints are part of the system, not an accident. If your interviewer nudges you, listen. Taking a hint is not penalized. Minor bugs are not, either. Meta values speed and forward progress more than bug-free first-pass code (which is a very production-minded trade).

The interview loop

5–6 rounds total. E6+ adds leadership assessment and architecture depth.

1

Recruiter Screen

30 min · Phone / Video

Role fit, location, timeline, basic background. Meta recruits aggressively on campus and via referrals.

2

Technical Phone Screen

45 min · CoderPadgate

2 easy-medium DSA problems. This is the main gate — fail here and the loop ends. Speed matters: ~15 min per problem.

3

Coding Round 1

40 min · Onsite / Virtualgate

2 problems, LeetCode easy-medium. Raw DSA execution. Meta optimizes for speed over polish — 15 min per problem target.

4

Coding Round 2 — AI-Assisted

60 min · Full IDEgate

Full IDE with terminal, file tree, unit tests, and an AI model dropdown. Llama 4 default — you can switch to GPT-4o mini, Claude, or Gemini. The #1 failure mode is blindly accepting AI suggestions.

5

Behavioral

45 min · Onsite / Virtual

Collaboration, project ownership, impact. Weight is lower at E3, rises with level. Need 1–2 quarter-long project stories at E5+.

6

System Design

45 min · E5+ only

Architecture, tradeoffs, APIs/data flow at Meta scale. Coding determines hire/no-hire; design determines level (E4 vs E5).

The AI-assisted round — what you actually need to know

One onsite coding round (60 min instead of the usual 40) gives you a full IDE environment: terminal, file tree, unit tests, and an AI model dropdown. The default model is Llama 4, but you can switch to GPT-4o mini, Claude Haiku/Sonnet, or Gemini 2.5 Pro.

The evaluation is judgment under AI assistance, not raw output. Interviewers watch whether you can critically evaluate AI suggestions, catch errors, and integrate them into a working solution. Blindly copy-pasting is the fastest way to fail.

This round began piloting in Q4 2025 and is rolling out across all SWE roles in 2026.

Difficulty breakdown

30% easy
55% medium
15% hard

55% medium and 15% hard, with 30% easy. The high medium percentage reflects Meta's two-problems-per-round format — they need problems that are solvable in 20 minutes each but still test real understanding. The low hard percentage is partly because DP is banned — which removes many of the hardest traditional interview questions.

Unlock the full guide

Complete walkthrough, diagrams, and practice problems — all included with StrongYes Pro.

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New grad entry (E3)

New grads enter at E3 (Software Engineer) with ~$173K median total comp: $139K base + $28.6K annualized stock + $6K bonus. Meta is one of the highest-volume new-grad hirers in tech.

What's different at E3:

  • No system design round. This is a major advantage over companies like Uber, which requires LLD/OO design even at L3.
  • Behavioral is lower weight — 1–2 solid project stories are usually enough.
  • Your loop is: recruiter screen → 45-min phone screen → onsite (Coding 1, AI-Assisted Coding 2, Behavioral). Three rounds on the onsite, not four.
  • Early-career comp is base-heavy and predictable — stock is only 17% of TC at E3 vs 63% at E6.
  • Expected progression: E3→E4 in 1.5–2 years, E4→E5 in 2–3 years. E5 is terminal level.

Interview culture

Candidates consistently report that Meta's process is highly standardized — less variance between teams than Apple or Netflix. 57% of Glassdoor respondents rate the experience as positive (difficulty 3.2/5).

The "move fast" ethos permeates the interview. Speed and execution velocity are valued above perfectionism, and interviewers are trained to give good hints rather than let candidates struggle silently.

Negative reports center on post-interview communication — rejection emails with no feedback and recruiter ghosting are recurring complaints. The behavioral round carries medium/low weight relative to coding, but E5+ candidates need at least a couple of quarter-long project stories to demonstrate scope.

Curated by Leo Kwan

This guide is AI-assisted editorial, reviewed and fact-checked by Leo Kwan. Interview data is aggregated from 12 public sources — not scraped or copied. Last updated April 2026.

Sources

  • interviewing.ioSenior engineer's guide to Meta's full loop, level differences, AI round, and process quirks
  • ExponentMeta SWE interview guide — loop structure, speed expectations, 2x question density
  • Levels.fyiCompensation by SWE level — TC, base, stock, bonus (212 submissions)
  • GeeksforGeeksCommon Meta system design questions and architecture themes
  • GlassdoorInterview experience ratings, difficulty, timeline (18K+ reviews)
  • CodingInterviewAIPattern-level breakdown of Meta DSA categories and speed prep
  • Yangshun Tay — Tech Interview HandbookOpen-source interview handbook maintained by Yangshun Tay (ex-Meta). Includes Meta-specific sections on behavioral prep, system design expectations, and the 40-minute coding-round tactical pattern
  • Gergely Orosz — Pragmatic EngineerFormer Uber senior engineer. Pragmatic Engineer covers Meta engineering culture, hiring process, and levels ladder. Newsletter goes deeper on Meta-specific posts; blog archive has the foundational framing
  • Andrew Bosworth — Loose ThinkingMeta CTO Andrew Bosworth writes publicly at boz.com. "Be Kind" is canonical reading for the cultural signal Meta interviewers look for: direct, collaborative, forward-moving. Read 3-4 Bosworth posts before an E5+ behavioral round
  • Gayle Laakmann McDowell — Cracking the Coding InterviewFormer Apple/Microsoft/Google software engineer. _Cracking the Coding Interview_ (6th ed) is the canonical algorithmic-interview prep text; its behavioral chapters and STAR-format story framework apply directly to Meta’s behavioral round
  • Meta Engineering BlogEngineering.fb.com — Meta’s public engineering writing. Architecture deep-dives on React (Jordan Walke), PyTorch, Hydra, Cassandra origins, and production-scale distributed systems. The source-of-truth for "what Meta actually builds" system-design questions reference
  • Will Larson — Work on What MattersFormer Uber/Stripe/Calm CTO. "Work on What Matters" essay and _An Elegant Puzzle_ / _Staff Engineer_ framings map directly to how Meta evaluates E5+ candidates for scope, cross-team impact, and senior-IC judgment
  • StrongYes internal editorial research and Codejeet corpus gap analysis