Meta runs a highly standardized loop that barely varies by office or level: a recruiter call, one timeboxed technical screen, then a 'full loop' of roughly four 45-minute rounds. For software engineers that loop is two coding rounds (two problems each, medium difficulty, solved fast in a non-executing CoderPad), one design round where candidates pick either Product Architecture or System Design, and one behavioral round mapped to Meta's own values. Non-SWE tracks keep the same skeleton but swap the middle: data engineers get combined 'full stack' rounds mixing product sense, data modeling, SQL and Python; production engineers get Linux internals and a troubleshooting scenario; research scientists get three coding rounds plus systems design; UX researchers get a hypothetical research-plan case. Downlevelling and follow-up rounds are common, and offers are followed by a separate team-matching stage that can add weeks or months.
These 12 writeups cover software engineering, production engineering, data engineering and other roles. 2 of them were posted under a pseudonym (Reddit, GeeksforGeeks or forum handles), so we could not verify the authors’ identities.
Typical rounds
4.51-6 range
Outcomes shared
5/5offer / not
Most common round
Technical
Sources span
2022 - 2026
Most frequently reported · Behavioral(10), Scalability(8), System design(8), STAR stories(7), Data structures & algorithms(6)
Meta Platforms’s official process
Meta says its process usually spans two to three months and has three phases: a recruiter conversation, an initial screening, and a full loop in which candidates meet peers, cross-functional partners and leaders. Technical rounds run in CoderPad across a wide language set, design rounds use CoderPad with Mermaid diagrams, and Meta now states that an in-interview AI assistant (Claude, ChatGPT, Gemini or Meta's own models) is present in many technical rounds. A companion page for machine-learning roles describes the full loop as up to six 45-minute conversations with engineers, and a UX research page describes the initial screen as a 45-minute conversation with a practising UX researcher about research process and rigor.
Data structures & algorithms·Arrays & strings·Trees·Graphs·Dynamic programming·System design·Scalability·API design·SQL·Operating systems·Networking·Debugging·Behavioral·STAR stories·Conflict handling·Past projects·Case study
Interview experiences at Meta Platforms
Outcome
Seniority
Software Engineer (E5)
Experienced
Received an offer6 rounds
1
Coding screenPhone screen
A 45-minute screen with two problems. The author lost most of the time to nerves on an easy linked-list question, then recovered and finished a shortest-path style graph question inside the remaining minutes. Passed, but the recruiter relayed that it was not a strong-hire signal.
Covered · Linked lists, Graphs, Data structures & algorithms
2
CodingTechnical
Two problems in 45 minutes: a string-manipulation question with hidden edge cases, then an array/hash-map pattern the author recognised but explained poorly, leaving the interviewer unconvinced by the approach.
Covered · Arrays & strings, Hashing
3
CodingTechnical
A smoother round with a queue-based problem followed by a familiar binary-tree pattern, both completed with time to spare.
Covered · Queues, Trees
4
Product ArchitectureSystem design
Design a feature for the Facebook app. Meta lets the candidate choose Product Architecture or System Design; the author picked Product Architecture as a backend engineer, drove requirements then API specs and core entities, and spent the back half on deep dives into scaling and consistency.
Covered · System design, API design, Scalability
5
BehavioralBehavioral
Situational questions where the interviewer repeatedly drilled into specifics of past projects, apparently to test that the claimed work was genuinely the candidate's.
Covered · Behavioral, STAR stories, Past projects
6
Follow-up codingTechnical
Because one coding round graded poorly, the hiring committee ordered an extra coding interview rather than rejecting. Two problems: a binary-tree traversal variant and a string problem needing a stack, both completed.
A 45-minute screen where the author reports being expected to get through two to three problems: an array question plus an extension, then a tree question. The recurring theme is speed, with roughly 35 usable minutes.
Covered · Arrays & strings, Trees
2
CodingTechnical
A topological-sort problem solved with careful dry-running, followed by a heap problem where the candidate offered several approaches but ran out of time before reaching the optimal one.
Covered · Graphs, Heaps
3
CodingTechnical
Three questions: a binary-search problem that looked like dynamic programming, a disjoint-set-union problem, and a short string/sorting question introduced in the last five minutes that there was no time to code.
Design a feature for Instagram. Requirements first, then functional and non-functional constraints including the celebrity fan-out case, a horizontally scaled high-level design, then the interviewer pushed into low-level detail on APIs, client-side optimisation and schema.
Covered · System design, Scalability, API design, DBMS
5
BehavioralBehavioral
Past project work framed against Meta's stated values, plus situational questions on handling conflict, owning mistakes and taking initiative.
Covered · Behavioral, STAR stories, Conflict handling, Past projects
A palindromic-string question and a permutations question with a third follow-up. Passed, with written feedback that naming conventions needed work and the code was too deeply nested.
Covered · Arrays & strings, Backtracking
2
CodingTechnical
An easy two-pointer question that still cost the candidate time because the code came out messy, then a lowest-common-ancestor tree problem where the interviewer rejected two suggested approaches and pushed for a trick the candidate did not know. Self-assessed as the round that sank the loop.
Covered · Two pointers, Trees
3
CodingTechnical
A DFS-on-tree problem and a sliding-window variant, both solved optimally and in time. The one stumble was being unable to answer well when asked what test cases they would run.
Covered · Trees, Graphs, Sliding window
4
Product ArchitectureSystem design
A file-storage product design. The candidate ran a fixed framework: functional requirements, non-functional requirements, capacity numbers, APIs, data models, high-level design, then deep dives and user experience.
Covered · System design, API design, Scalability
5
BehavioralBehavioral
Situational questions the author characterises as skewing toward negative framings (failures, disagreements). They prepared roughly 30-40 stock questions with prepared stories and a STAR variant that adds a reflection step.
Covered · Behavioral, STAR stories, Conflict handling
Four medium coding questions in one hour, sent about a week after an unreferred portal application.
Covered · Data structures & algorithms
2
CodingTechnical
45 minutes over Zoom in CoderPad: a medium question solved in around 15 minutes, then a harder follow-up in 25, each closed out with a dry run, complexity discussion and edge cases.
Covered · Data structures & algorithms
3
CodingTechnical
Same 45-minute two-problem shape, with the harder question first this time.
Covered · Data structures & algorithms
4
BehavioralBehavioral
Standard behavioral questions plus discussion of internship experience. The author felt underprepared here (it landed during semester exams) and the rejection followed a week later despite two strong coding rounds.
Two problems: reducing a string to a palindrome by deletion, and evaluating a simple arithmetic expression restricted to addition and multiplication. Positive feedback landed within two to three days and the onsite was booked three weeks out.
Covered · Arrays & strings, Recursion
2
CodingTechnical
A four-directional shortest-path-in-a-grid problem, then a twist on sorted insertion into a circular linked list where only an arbitrary node pointer is given rather than the head, with repeated inserts to consider.
Covered · Graphs, Linked lists
3
CodingTechnical
A vertical-order binary tree traversal, then merging three sorted arrays while dropping duplicates, where the interviewer's bar was clean readable code rather than just a working answer.
Covered · Trees, Arrays & strings, Sorting
4
System designSystem design
Design a web crawler, self-driven, with the discussion centring on trade-offs and on avoiding recrawling the same page within an iteration.
A 30-minute call covering technical background, role fit and location preference, plus prep resources. Came a few weeks after a direct LinkedIn application, no referral.
Covered · Resume deep-dive
2
Technical screenTechnical
One hour in CoderPad with a Meta data engineer, split into roughly 25 minutes of SQL against provided schemas and 25 minutes of Python. No code execution, so everything is written in plain text and reasoned through aloud.
Covered · SQL, Python, Data structures & algorithms
3
Full stack round (x3)Panel
Three one-hour rounds, each split four ways: product sense on a Meta surface, then a dimensional data model (facts, dimensions, keys, relationships) supporting the metrics just defined, then analytical SQL on that schema, then a practical Python question on streaming input rather than a classic algorithm puzzle.
Covered · Product metrics, Data modeling, SQL, Python
4
OwnershipHiring manager
A 30-minute manager conversation of five or six questions with follow-ups about past work and projects; can be scheduled either before or after the technical block.
Covered · Behavioral, Past projects
5
Team matchingHiring manager
After passing, a short call flow with managers in the preferred location to find a team with open headcount.
A CoderPad round with no code execution, structured around a single business theme (ad signal quality) rather than a grab bag of questions. Given related tables, the candidate had to define the meaningful metrics themselves, then write the SQL that answers them and interpret the result as a product insight.
Built around Meta's stated values, with questions on handling conflict, prioritising across projects and disagreeing with a colleague.
Covered · Behavioral, STAR stories, Conflict handling
6
Systems designSystem design
A deliberately practical design problem rather than the abstract whiteboard-a-Twitter format; the author notes the expectation is a concrete, operationally grounded solution.
Two coding tasks (parsing a CSV file and manipulating the rows, plus an easy string-transformation puzzle) followed by a live troubleshooting exercise framed as a broken website, where the interviewer kept shifting the constraints until the candidate traced it to a full disk.
Covered · Arrays & strings, File I/O, Debugging
2
CodingTechnical
Another file-parsing problem, this time with a chain of follow-ups probing whether the solution could be optimised and extended.
Covered · File I/O, Arrays & strings
3
System designSystem design
A production-engineering flavoured design question. The author rates this as their weakest round and says generic system-design prep did not cover the PE-specific concerns.
Covered · System design, Scalability
4
LinuxTechnical
Breadth questions across memory management, processes, file systems, security basics and networking fundamentals.
45 minutes with about 35 usable for a single medium-difficulty algorithm problem, bookended by a short intro and candidate questions.
Covered · Data structures & algorithms
2
Coding (x3)Technical
Three separate coding rounds, two medium problems each. The author stresses that clarifying constraints up front, using descriptive names and stepping through the code literally rather than as intended is what the interviewers actually score.
Covered · Data structures & algorithms, Testing
3
Systems designSystem design
A standard architecture problem in the same 45-minute frame; prepared for with public system-design material rather than anything research-specific.
Covered · System design, Scalability
4
BehavioralBehavioral
Run by a research scientist and focused on the candidate's PhD work; the author deliberately treated it as a conversation with prepared stories to drill into rather than as scripted STAR answers.
Covered · Behavioral, Past projects, Resume deep-dive
About 20 minutes on CV, research background and career goals, with the recruiter naming the format of the next round in advance.
Covered · Resume deep-dive
2
Research caseTechnical
The candidate picks a consumer app, then gets a hypothetical stakeholder question about why users prefer it or a competitor, and has around 40 minutes to talk through how they would design and run a study answering it inside a three-week window. Rejected here; the candidate attributes it to vague, unstructured answers rather than lack of method knowledge.
Covered · Case study, Research methods, Product metrics
What is the interview process like at Meta Platforms?
Meta runs a highly standardized loop that barely varies by office or level: a recruiter call, one timeboxed technical screen, then a 'full loop' of roughly four 45-minute rounds. For software engineers that loop is two coding rounds (two problems each, medium difficulty, solved fast in a non-executing CoderPad), one design round where candidates pick either Product Architecture or System Design, and one behavioral round mapped to Meta's own values. Non-SWE tracks keep the same skeleton but swap the middle: data engineers get combined 'full stack' rounds mixing product sense, data modeling, SQL and Python; production engineers get Linux internals and a troubleshooting scenario; research scientists get three coding rounds plus systems design; UX researchers get a hypothetical research-plan case. Downlevelling and follow-up rounds are common, and offers are followed by a separate team-matching stage that can add weeks or months.
What topics does Meta Platforms test in interviews?
Commonly reported topics include Data structures & algorithms, Arrays & strings, Trees, Graphs, Dynamic programming, System design.
These guides summarize public, first-hand interview experiences shared by candidates. They describe the shape of each loop and the topics that came up, not a leaked question bank, and every experience links back to its original source. Processes change often; treat this as directional prep, not a script.