Meta (Facebook) Interview Preparation
Coding, System Design & Leadership and Drive
Pakkeprisene nedenfor er i amerikanske dollar (USD). Disse handlekurvlenkene går til den engelske betalingssiden, der du betaler i USD. Øvingsoppgavene og de fleste kursene er på engelsk.
Land guiden gjelder: United States · Technology
Ansettelsesprosessen kan variere med land, stilling, avdeling og år.
Meta hires candidates who can move fast, build awesome things, and architect systems for billions of users. The process features intense live coding interviews, system design at massive scale, and a deep behavioral interview assessing cultural alignment with Meta's values.
Ansettelsesprosessen
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1Recruiter Screen Oppgitt av arbeidsgiverenInitial call to assess baseline fit, motivation, and logistics→ Prepare concise overview of experience and motivation for Meta specifically
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2Technical Phone Screen Oppgitt av arbeidsgiverenLive coding interview testing data structures and algorithms→ Practice coding while talking through your approach aloud
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3Interview Loop (Final) Oppgitt av arbeidsgiverenMultiple rounds covering coding, system design (mid-senior), and behavioral (Leadership and Drive / Jedi). Virtual or onsite.→ Prepare for all three dimensions: coding, system design, and behavioral
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4Hiring Committee Oppgitt av arbeidsgiverenCentralized committee reviews all interview feedback to make a decision→ No direct action — ensure strong performance across all loop interviews
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5Team Matching Oppgitt av arbeidsgiverenAfter hiring committee approval, candidates match with specific teams→ Research teams and products you're interested in joining
Tester og vurderinger
Live coding interview where candidates solve algorithmic problems in real-time while communicating their thought process. Typically 45 minutes with 1-2 problems.
Måler: Data structures and algorithms proficiency, code quality, time/space complexity analysis, communication while coding
- Practice coding while speaking your thought process aloud
- Always state time and space complexity of your solution
- Start with brute force, then optimize
- Write clean, readable code — Meta values craftsmanship
Vanlige feil
- Coding silently without explaining your approach
- Not analyzing complexity
- Jumping to code without clarifying the problem first
- Writing messy, unstructured code
Intervjuer
Intensive coding rounds where candidates must solve complex data structures and algorithms problems optimally under tight time constraints (often 20 minutes per problem). Clear communication of time and space complexity is essential.
Format: 45 minutes, live coding, 1-2 problems
Hva intervjuere ser etter
- Optimal solutions (not just working code)
- Clear time/space complexity analysis
- Clean, bug-free code written quickly
- Strong communication while coding
- Ability to handle follow-up variations
Temaer du kan øve på
- Arrays and strings
- Trees and graphs
- Dynamic programming
- BFS/DFS
- Linked lists
- Think out loud — the interviewer wants to understand your reasoning
- Clarify constraints and edge cases before coding
- Test your solution with examples before declaring done
- Be prepared for optimization follow-ups
Candidates architect solutions at 'Meta scale,' proactively addressing sharding, caching, load balancing, and API design. Prompts frequently map to real Meta products (e.g., designing a news feed or messenger).
Format: 45 minutes, whiteboard/virtual design discussion
Hva intervjuere ser etter
- Ability to operate at massive scale (billions of users)
- Proactive identification of bottlenecks
- Knowledge of sharding, caching, load balancing, CDN, API design
- Clear trade-off discussions
- Structured approach to system architecture
Temaer du kan øve på
- Design a news feed
- Design a messenger system
- Design a photo/video sharing platform
- Design a notification system
- Design a content recommendation system
- Start with requirements and constraints before jumping to architecture
- Always discuss scale — think billions of users
- Proactively address caching, sharding, and load balancing
- Study architectures of Facebook, Instagram, WhatsApp
Deep behavioral interview that aggressively evaluates conflict resolution, ownership, and alignment with Meta's core values. Called 'Jedi' internally. Searches for evidence of Move Fast, Focus on Long-Term Impact, and Build Awesome Things.
Format: 45 minutes, behavioral interview using STAR method
Hva intervjuere ser etter
- Bias toward action and speed
- Ownership and accountability
- Ability to navigate ambiguity
- Direct communication and feedback acceptance
- Evidence of building impactful things
- Conflict resolution
Temaer du kan øve på
- Tell me about a time you moved fast to ship something impactful
- Describe a conflict with a colleague and how you resolved it
- When did you make a hard decision with incomplete information?
- Tell me about your most impactful project
- Prepare stories demonstrating fast, decisive action
- Show how you shipped products/results with real impact
- Include examples of navigating ambiguity
- Demonstrate openness to direct feedback
Forskjeller mellom stillinger
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Software Engineering
Tester og vurderinger
- Technical phone screen
Intervjuer
- 2 coding interviews (data structures & algorithms)
- 1 system design (mid-senior+)
- 1 behavioral (Leadership and Drive / Jedi)
Product Management
Tester og vurderinger
- Product sense case (some processes)
Intervjuer
- Product sense interview
- Execution/metrics interview
- Leadership and Drive
- System design (technical PM)
Data / Analytics
Tester og vurderinger
- SQL/coding assessment (role-dependent)
Intervjuer
- Technical data analysis interview
- Product analytics questions
- Behavioral interview
Experienced Technical (Staff+)
Tester og vurderinger
- Technical screen
Intervjuer
- System design (heavy weighting)
- Coding interviews
- Leadership and Drive (deeper probing)
- Architecture review
Velg en øvingspakke for stillingen din
Meta's process is famously standardized: engineers get two coding rounds with roughly twenty minutes per problem, system design from E4, and the Leadership and Drive interview - the Jedi - before a centralized hiring committee and team matching. Because the loop is so predictable, preparation compounds: you can rehearse exactly the format you will face. Line up your application with a family below and rehearse the loop format its teams have standardized.
Software Engineer (E3-E6, Family of Apps)
Software EngineeringMeta software engineers build Facebook, Instagram, WhatsApp and Messenger at billion-user scale, inside a monorepo culture where Move Fast is a literal engineering practice - ship cycles are short and code review is the safety net. From E4 you join system design rounds; from E5 you lead design conversations across teams. Hackathons, internal tools and a famously high developer-velocity culture define the day to day.
Slik ansetter Meta til denne typen stilling: After a 45-minute technical phone screen with one or two DSA problems, the loop is fixed: two coding rounds at roughly twenty minutes per problem, one system design round from E4, and the Leadership and Drive (Jedi) behavioral interview. A centralized hiring committee reviews everything, then team matching happens after approval.
Hvorfor denne pakken: Meta coding rounds are speed tests first - two problems per round at about twenty minutes each - so timed programming practice at that cadence is the single most honest rehearsal available. JavaScript and Python are the most common interview languages for front-end and generalist loops, and SQL shows up in product-adjacent rounds. The Jedi round demands quantified ownership and conflict stories, which interview prep exists to manufacture. Inductive pattern work keeps E3 problem solving flexible, and senior loops weigh design trade-off defense and cross-team judgment, where critical and situational drills apply.
E3 loops are coding-dominant: speed and pattern flexibility in one language come before design work.
E4-E5 loops add system design and product context to the speed core.
E5-E6 loops weigh design leadership, trade-off defense and Jedi depth.
Production Engineer (PE)
Production Engineering & InfrastructureProduction Engineers are Meta's version of SRE: they build and run the infrastructure behind the Family of Apps - fleets, networks and capacity at global scale. The work is kernel-and-service-level debugging, performance tuning and global traffic management, with Python as the standard tooling language. PE differs from SWE in weighting systems knowledge more heavily than algorithmic polish.
Slik ansetter Meta til denne typen stilling: PE interviews split into coding plus systems domains: operating systems, networking and performance. The signature round is scenario debugging of production-like systems - you walk a broken system to root cause live - plus the standard Jedi behavioral round.
Hvorfor denne pakken: Systems debugging under partial information is applied deduction, so deductive drills are the closest rehearsal format for the signature round. Coding rounds still apply and Python is the PE tooling language, so that course plus timed practice covers both halves. Security fundamentals surface in access-control and blast-radius questions, and numerical work supports capacity and traffic arithmetic. Senior PE loops revolve around incident-command and risk-acceptance judgment, where critical and situational drills structure better answers.
Entry PE loops stress coding plus OS and networking fundamentals.
Mid-level loops expect owned systems and debugging narratives with follow-through.
Senior loops weigh incident command, risk acceptance and fleet-level judgment.
Machine Learning Engineer / Research Scientist
AI & Machine LearningMeta's ML engineers and research scientists work on ranking and recommendations for Feed and Reels, and on the PyTorch-and-Llama era of GenAI development, training on custom MTIA silicon and Grand Teton superclusters. FAIR and the GenAI orgs publish research while shipping to products with billions of users - an unusual dual mandate that shapes what interviews probe.
Slik ansetter Meta til denne typen stilling: Expect a coding screen plus an ML depth round covering training, evaluation metrics and recommendation systems. Research roles add paper deep-dives and open-ended problem solving, and the Jedi behavioral round is standard across the family.
Hvorfor denne pakken: ML interviews here drill training loops, loss choices and evaluation - the direct content of the ML course - while GenAI vocabulary around agents, retrieval and evals is now expected in Meta AI loops specifically. Probability and statistics questions appear in modeling screens, and coding speed still decides the screen, so the timed programming module stays in the bundle. Senior loops weigh modeling trade-off defense and responsible-AI judgment, where risk framing and situational drills earn their slots.
Entry screens stress coding plus ML fundamentals before research depth.
Mid-level loops expect models you trained and shipped with evals you own.
Senior loops weigh modeling strategy, infrastructure trade-offs and Jedi depth.
Data Scientist, Product Analytics
Data Science & AnalyticsMeta Data Scientists embed with product teams across Facebook, Instagram and WhatsApp to define metrics, design experiments and explain movement. SQL fluency is mandatory and Python shows up for causal inference and simulation work. The ladder splits into Analytics and Inference tracks, but both live close to product decisions and both face the same hiring committee.
Slik ansetter Meta til denne typen stilling: The technical screen is SQL plus a product metrics case - the classic debug-why-traffic-dropped shape. The loop adds a product analytics case, a lighter technical round and the Jedi behavioral, then the same hiring committee and team matching engineers face.
Hvorfor denne pakken: SQL screens are explicit and time-boxed, so the SQL course is direct preparation. Debug-the-metric cases are hypothesis-testing exercises on product data, which the statistics modules teach in exactly the shape asked, and business analytics framing strengthens the metric-decomposition answers that decide the case. Numerical speed supports live arithmetic, and senior DS loops move toward measurement strategy and risk calls, where risk framing and judgment drills apply.
Entry screens stress SQL correctness and structured case decomposition.
Mid-level loops expect experiments you designed and metric moves you explained.
Senior loops weigh measurement strategy and cross-team influence.
Product Manager (Meta Apps + Reality Labs)
Product ManagementMeta PMs own surfaces across Facebook, Instagram and WhatsApp plus Reality Labs products - Quest, Ray-Ban Meta glasses and Horizon. The culture is execution-first: PMs move with engineer-heavy teams and ruthless prioritization, and Reality Labs PMs additionally handle developer ecosystems and hardware-software trade-offs that pure software PMs never see.
Slik ansetter Meta til denne typen stilling: The PM loop is standardized around Product Sense (design-X questions) and Execution (metrics, debug, prioritize) interviews plus the Jedi behavioral. Some technical PM roles add system design, and team matching follows hiring-committee approval rather than preceding it.
Hvorfor denne pakken: Execution interviews are metric-math and prioritization drills under a clock, which numerical practice plus structured decomposition cover directly. Product Sense scores user centric structured reasoning, the exact target of critical drills. GenAI product vocabulary increasingly appears in Meta PM loops as AI features spread across the apps, and analytics framing strengthens execution cases. Senior PM loops weigh strategy, risk and resourcing trade-offs, where the risk and FP&A courses carry weight.
Entry PM loops stress structure in Product Sense and clean execution math.
PM loops expect metric moves you drove and prioritization you can defend.
Senior loops weigh strategy, resourcing judgment and Jedi depth.
Technical Program Manager (Infra & Product)
Technical Program ManagementMeta TPMs drive cross-team execution: infrastructure rollouts, privacy programs and data-center launches, with heavy dependency management across engineering orgs and daily escalation judgment. Reality Labs TPMs additionally coordinate hardware builds against software milestones, where a slipped mold or display shipment moves a whole program.
Slik ansetter Meta til denne typen stilling: The TPM screen covers program scenario judgment plus technical fundamentals. The loop adds a program management case, a technical round and the Jedi behavioral, and written communication is often assessed through scenario responses you compose on the spot.
Hvorfor denne pakken: Scenario rounds are situational judgment problems with technical context, so the SJT module is the format match, and critical drills structure the decomposition interviewers score. Cost and schedule defense maps to project cost control vocabulary, and enough technical literacy to hold credibility in the technical round comes from the Python course. Senior TPM loops respect formal program frameworks - PMP scope - and reward risk framing on multi-team calls.
Entry TPM loops stress structured thinking and technical basics.
Mid-level loops center on programs you ran and escalations you resolved.
Senior loops weigh cost and risk defense plus formal program depth.
Product Designer / UX Researcher
Design & UX ResearchMeta product designers shape the core app surfaces and Horizon OS, working within internal design systems and a critique-heavy culture. UX Researchers run foundational and evaluative studies across global markets, and Reality Labs design work extends into 3D and spatial interfaces that have few settled conventions to copy from.
Slik ansetter Meta til denne typen stilling: The loop is a portfolio review plus app-critique or design exercise rounds; research roles add a methods deep-dive and a research case. The Jedi behavioral round is standard across design hiring too.
Hvorfor denne pakken: Critique rounds test abstract and spatial reasoning - hierarchy, pattern, arrangement - which the abstract module drills directly. Quantitative research fluency genuinely strengthens UXR loops, since Meta expects research to land in metrics as well as insight, and communicating rationale under friendly fire is a verbal task in practice. Senior design rounds shift toward strategy and data-informed judgment, where analytics and risk framing carry weight.
Entry design loops stress craft, critique resilience and process narrative.
Mid-level loops dig into shipped surfaces and the trade-offs behind them.
Senior loops weigh strategy, spatial and systems judgment, and influence.
Client Partner / Account Manager (Meta Ads)
Sales & Client PartnershipsMeta's Global Business Group sells advertising to the largest advertisers in the world, while SMB teams serve small-business clients at scale. Client Partners own account revenue; Account Managers run campaign strategy and optimization; and both need genuine auction and bidding knowledge, including Advantage+ automated campaigns, to stay credible with sophisticated buyers.
Slik ansetter Meta til denne typen stilling: Sales loops include mock client calls, strategy cases and presentation rounds. Analytics questions on campaign metrics are common, and the behavioral round probes Move Fast behavior and impact stories with numbers attached.
Hvorfor denne pakken: Campaign math - CPM, ROAS, budget pacing - is numerical reasoning under time pressure, which the numerical module drills in exactly that shape. The sales course covers discovery and objection handling for the mock call, and reading campaign dashboards live is a data-analysis task. Senior commercial roles own forecasts, budgets and book-of-business risk, and FP&A plus risk coursework speaks to that remit.
Entry commercial loops test structure, curiosity and campaign-math basics.
Experienced loops center on a mock client call and campaigns you grew.
Senior loops weigh book strategy, forecast ownership and risk judgment.
Hardware Engineer (Reality Labs: Quest, AR Glasses)
Hardware & Reality Labs EngineeringReality Labs hardware engineers build Quest headsets, Ray-Ban Meta smart glasses and the custom silicon behind them. Disciplines span electrical, optics and photonics, mechanical, and display and sensing integration, on a consumer cadence that runs through ODM and partner supply chains. The problems are unusual - thermal budgets, optical geometry and weight limits interact in ways mainstream consumer hardware rarely forces.
Slik ansetter Meta til denne typen stilling: The technical screen hits discipline fundamentals - circuits, thermal or tolerancing depending on your specialty. Onsites add a design exercise under real constraints, partner and ODM trade-off questions, and the standard Jedi behavioral round.
Hvorfor denne pakken: EE and optics screens rest on circuits and electromagnetics fundamentals, which those two modules teach directly. Mechanical reasoning supports packaging and thermal questions, physics keeps optical and energy arguments honest, and spatial reasoning genuinely helps with optics-adjacent and industrial-design problems. Senior hardware loops turn on supplier and schedule trade-offs, where risk framing earns its slot.
Graduate loops stress discipline fundamentals and fast math.
Mid-level loops assume shipped hardware: tolerancing and ODM war stories.
Senior loops weigh architecture, supplier strategy and risk judgment.
People Partner / Technical Recruiter
People & RecruitingMeta's People organization supports a distributed workforce, and its recruiters run some of the highest-volume engineering pipelines in the industry. People Partners handle performance cycles, compensation calibration and org design directly with leaders, and recruiting coordination keeps loop logistics running for thousands of interviews weekly.
Slik ansetter Meta til denne typen stilling: Behavioral interviews are anchored in Meta's values - speed, impact and openness to feedback - and recruiter screens include mock candidate conversations and sourcing strategy exercises. Expect situational judgment on sensitive workplace scenarios too.
Hvorfor denne pakken: Workplace scenarios here are SJT-format problems with real sensitivity around performance and calibration, so that drill is the closest rehearsal. Verbal precision supports stakeholder communication screens, and SHRM-level knowledge genuinely differentiates senior People Partner candidates. Data fluency helps as people decisions increasingly reference metrics, and risk framing supports the senior end of the ladder where organizational calls carry consequence.
Entry loops are behavioral-first, anchored in values stories.
Experienced loops probe cycles, calibrations and pipelines you ran.
Senior loops add policy depth, people analytics and risk judgment on organizational calls with real consequence.
Verdier og rammeverk
Meta's culture is driven by specific core values that define how employees work. The behavioral interview systematically searches for evidence of these values in your past experiences.
- Show speed and decisiveness in your examples
- Demonstrate long-term thinking alongside fast execution
- Emphasize building quality products with real user impact
- Show openness to feedback and transparent communication
- Demonstrate forward-thinking and innovation
Forslag til øvingsmoduler
Øvingsplaner
- Solve 3-4 LeetCode Medium problems (arrays, strings, trees)
- Review Meta's core values (Move Fast, Focus on Long-Term Impact, etc.)
- Prepare 2 strong STAR stories for the Leadership and Drive interview
- If system design: review one system architecture (news feed or messenger)
- Daily coding practice (5+ problems per day), focus on optimal solutions
- Prepare 4 STAR stories aligned to Meta values
- Practice coding while thinking aloud (record yourself)
- If system design: study sharding, caching, load balancing patterns
- Research Meta's recent products and technical challenges
- Daily coding practice (3-5 problems) covering all major categories
- System design: study 3+ architectures at Meta scale
- Prepare 5+ STAR stories covering Move Fast, Impact, and conflict
- Practice mock coding interviews with strict 20-minute time limits
- Study Meta's engineering blog for technical context
- Conduct mock behavioral interviews focused on ownership and speed
- Practice time/space complexity analysis for every solution
- Systematic daily coding practice (30+ problems total) at Medium-Hard level
- Master system design patterns: news feed, messenger, photo sharing, notifications
- Develop comprehensive STAR story bank (8+ stories) aligned to all Meta values
- Conduct multiple full mock interview loops (coding + system design + behavioral)
- Study Meta's tech stack and recent engineering challenges
- Practice explaining complex architectures clearly within 45 minutes
- Refine weakest coding areas based on practice performance
- Practice receiving and responding to feedback in mock interviews
- Build confidence in ambiguity — practice open-ended scenarios
Vanlige spørsmål
Kilder og kontrollstatus
2 kilder · 2 fra arbeidsgiveren eller en annen primærutgiver · 2 omtalt, men ikke bekreftet
Se hva hver kilde dekker
- Arbeidsgiverens nettsted Meta interview process and cultural values Omtalt andre steder, ikke oppgitt av arbeidsgiveren
- Arbeidsgiverens nettsted Meta Careers - Preparing for Your Software Engineering Interview Omtalt andre steder, ikke oppgitt av arbeidsgiveren
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