Join Meta and build products that connect billions. Shape the future of social connection, AR/VR, and AI.
Founded
2004
Employees
70,000+
Daily Users
3.2B+
Glassdoor
4.1 ★
₹30 LPA - ₹3 Cr+
Salary Range
4-8 Weeks
Interview Process
5-6 Rounds
Total Interviews
~0.5-1%
Acceptance Rate
Meta, founded by Mark Zuckerberg in 2004 as Facebook, has grown from a college social network into one of the world's most influential technology companies. In October 2021, the company rebranded to Meta to reflect its expanded vision beyond social media into the metaverse.
Today, Meta operates a family of apps that connect 3.2+ billion people daily: Facebook, Instagram, WhatsApp, and Messenger. The company's Reality Labs division is pioneering AR/VR technology with Quest headsets and Ray-Ban smart glasses, working toward a future of immersive computing.
Meta's India presence includes offices in Gurugram, Hyderabad, and Bangalore, with thousands of engineers working on core products, ads, infrastructure, and AI. India is a strategic market (500M+ users) and a key engineering hub.
"Give people the power to build community and bring the world closer together."
The principles that guide how Meta builds and operates
Ship quickly, iterate rapidly, and learn from real-world feedback. Speed creates value.
Build things that matter at scale. Think in terms of billions of users and years of impact.
Craft high-quality products you're proud of. Engineering excellence matters.
Share information freely. Internal transparency enables better decision-making.
Take risks, challenge assumptions, and pursue ambitious goals. Safe choices don't change the world.
Understand where technology and society are headed. Build for tomorrow, not just today.
Explore different products and domains across the Meta family
Core Facebook experience: News Feed, Stories, Groups, Events, and social interactions for 3B+ users.
Build features for 2B+ users: Reels, Stories, Shopping, Creators, and visual discovery.
World's largest messaging platform: E2E encryption, payments, business messaging at scale.
Cutting-edge AI research: LLaMA, PyTorch, computer vision, NLP, and AI infrastructure.
Building the metaverse: Quest VR, Ray-Ban glasses, Horizon Worlds, and future computing.
Powers 98% of Meta's revenue. Ad targeting, measurement, shopping, and creator monetization.
Run Meta at global scale: data centers, networks, TAO (graph database), and internal tools.
Protect billions of users: content moderation, anti-abuse, misinformation, and security.
Among the highest-paying companies globally
E3 (Entry)
₹30-45 LPA
E5 (Senior)
₹90-140 LPA
E6+ (Staff)
₹1.4-3+ Cr
Including base, RSUs, and bonus components
| Role | Level | Experience | Total CTC | Base | RSUs |
|---|---|---|---|---|---|
| Software Engineer (E3) | E3 | 0-2 years | ₹30-45 LPA | ₹22-32 LPA | ₹6-10 LPA |
| Software Engineer (E4) | E4 | 2-5 years | ₹50-80 LPA | ₹38-55 LPA | ₹10-20 LPA |
| Senior SWE (E5) | E5 | 5-10 years | ₹90-140 LPA | ₹60-90 LPA | ₹25-40 LPA |
| Staff Engineer (E6) | E6 | 10-15 years | ₹1.4-2 Cr | ₹90-120 LPA | ₹45-70 LPA |
| Sr Staff Engineer (E7) | E7 | 15+ years | ₹2-3+ Cr | ₹1.2-1.5 Cr | ₹70-120 LPA |
| Product Manager (IC4) | IC4 | 3-6 years | ₹55-85 LPA | ₹40-60 LPA | ₹12-20 LPA |
| Senior PM (IC5) | IC5 | 6-10 years | ₹95-150 LPA | ₹65-95 LPA | ₹25-45 LPA |
| Data Scientist (IC4) | IC4 | 3-6 years | ₹55-90 LPA | ₹40-62 LPA | ₹12-22 LPA |
| Engineering Manager | M1 | 10+ years | ₹1.5-2.2 Cr | ₹95-130 LPA | ₹50-80 LPA |
| Research Scientist | IC4-IC5 | 3-8 years | ₹70-130 LPA | ₹50-85 LPA | ₹16-35 LPA |
Step-by-step guide to crack Meta interviews in 2026
Initial call with recruiter to discuss background, role fit, and interview expectations.
Coding interview via CoderPad. One medium-hard algorithm problem with focus on optimal solutions.
First coding round focusing on data structures and algorithms. Expect follow-up questions.
Second coding round with different problem type. May involve strings, DP, or combinatorics.
Design scalable systems for E4+. Design Facebook-like features: News Feed, Messenger, Stories.
Assess Meta Core Values fit. Questions about collaboration, feedback, and impact.
All interview feedback reviewed by hiring committee. Decision made within 1-2 weeks.
Pro tips from engineers who cracked Meta interviews
Meta interviews are DSA-heavy. Solve 200+ problems, focusing on medium-hard. Trees, graphs, DP, and strings are common.
Study GraphQL, TAO, Cassandra, and React for system design. Understand how Meta handles billions of requests.
Prepare STAR stories for Move Fast, Be Bold, Focus on Impact. Meta heavily weights cultural alignment.
Meta loves metrics. "Increased DAU by 5%", "Reduced latency by 200ms", "Scaled to 10M users".
Referrals significantly increase interview chances and expedite process. Network with Meta employees.
Meta uses CoderPad for coding. Practice writing complete, bug-free code in this environment.
Common questions about Meta careers and interviews
Start your journey at the company building the future of connection
Interview pages rank better when comparison, salary, and practice intent stay tightly connected.
Compare salary, culture, and interview difficulty side by side.
Read real student experiences before a specific interview loop.
Generate role-specific questions to practice beyond static lists.
See how a top product-company guide is structured end to end.
Company pages are strongest when they help readers prepare without pretending every interview loop is identical. We review employer-owned information first, then layer in patterns from verified candidate submissions and public hiring signals.
Reviewed by
Sproutern Company Research Team
Editors reviewing interview patterns, hiring flows, and public company guidance
Last reviewed
March 6, 2026
Freshness checks are recorded on pages where the update is material to the reader.
Update cadence
Rolling refreshes as interview patterns, salary signals, and hiring flows evolve
Time-sensitive topics move faster when rules, deadlines, or market signals change.
We distinguish between employer-owned facts and candidate-reported experience. If the company states it publicly, we treat it as a primary source. If the insight comes from candidate reports, we present it as directional preparation guidance rather than a guaranteed script.
We rely on employer-owned material first when summarizing application flow, interview stages, or role expectations.
Candidate reports are checked for plausibility, recency, and consistency before they influence evergreen guides.
Salary and hiring commentary is triangulated using multiple public references rather than a single anecdotal datapoint.
Added named authorship and reviewer context to company hubs
Company pages now make it easier to see who maintains the guidance, how candidate signals are treated, and where readers should verify employer-owned facts.
Interview-pattern corrections
When fresh reports conflict with older guidance, we review the employer-owned signal first and then update the preparation notes accordingly.