Download free Meta placement papers 2025 with DSA questions and solutions. Access coding problems, system design, interview process, eligibility criteria, and complete preparation guide.
Meta is a global leader in social media, virtual reality, and AI. Meta owns Facebook, Instagram, WhatsApp, and Oculus, and is pioneering the metaverse with cutting-edge technology. Meta India’s engineering teams work on products that impact billions, with a strong focus on innovation, scale, and impact.
Headquarters: Menlo Park, California, USA
Employees: 70,000+ globally
Industry: Social Media, VR, AI
Revenue: $134+ Billion USD (2023)
Academic Requirements
Academic Record: No strict cutoff; typically 7.0+ CGPA or 70% and above in 10th, 12th, and graduation, but strong coding skills matter most
Degree: B.Tech/B.E./M.Tech/MCA in CS, IT, ECE, or related fields
Year of Study: Final year students and recent graduates (within 1 year)
Backlogs: No active backlogs at the time of application
Branch Eligibility
Eligible Branches: CS, IT, ECE, EE, and related engineering streams
Programming Focus: Strong skills in Data Structures, Algorithms, and System Design
Experience: Freshers and up to 2 years experience (for E3/Software Engineer)
Additional Criteria
Coding Skills: Proficiency in at least one language (Python, C++, Java)
Gap Years: Maximum 1 year gap allowed
Course Type: Full-time degrees only
Nationality: Open to Indian and international students (for India roles)
Access free Meta placement papers PDF and Meta previous year question paper with detailed solutions. Download Meta last year question paper and Meta question paper PDF from previous years with comprehensive question banks covering DSA problems, coding questions, system design questions, and interview questions.
2024 Placement Papers PDF
Download Meta placement papers 2024 PDF with previous year DSA questions, coding problems, solutions, and exam pattern analysis.
2025 Placement Papers PDF
Download latest Meta placement papers 2025 PDF with current year DSA questions, coding problems, solutions, and updated exam patterns.
2026 Preparation Guide
Prepare for Meta placement 2026 with expected exam pattern, DSA questions, system design questions, and comprehensive preparation strategy.
What's Included
Complete Meta placement papers (2024-2026) with DSA questions, coding problems, system design questions, detailed solutions, answer keys, exam pattern analysis, and topic-wise organization.
Campus Recruitment
College Visits: Through placement cells at top engineering colleges
Direct Registration: Via college coordinators or Meta’s official campus drive announcements
Off-Campus Drives
Meta Careers Portal: Apply online for Software Engineer and other roles
Hackathons: Participate in Meta Hacker Cup and other coding contests
Referrals & Internships
Referrals: Internal referral program
Internship Conversion: PPOs for high-performing interns
Resume & Recruiter Screen (20-30 min)
Online Coding Assessment (OA) (60-90 min)
Technical Phone Screen(s) (1-2 rounds, 45 min each)
Virtual Onsite (Full Loop) (3-4 rounds, 45 min each)
HR/Offer Discussion
| Phase | Duration | Key Activities |
|---|---|---|
| Online Assessment | 1 day | Coding, debugging |
| Technical Interviews | 1-2 weeks | DSA, system/product design |
| Behavioral/Team Fit | 2-3 days | Meta values, teamwork |
| HR Discussion | Same day | Offer, negotiation |
| Result Declaration | 2-3 days | Offer letter, background check |
Practice with 30+ Meta placement paper coding questions covering arrays, strings, trees, graphs, and system design. These questions are representative of what you’ll encounter in Meta’s online assessment and technical interviews.
What’s Included:
Example: “abcabcbb” -> 3 (abc)
Code:
def lengthOfLongestSubstring(s: str) -> int: char_map = {} max_length = 0 start = 0 for end in range(len(s)): if s[end] in char_map and char_map[s[end]] >= start: start = char_map[s[end]] + 1 char_map[s[end]] = end max_length = max(max_length, end - start + 1) return max_lengthExample: nums = [2, 7, 11, 15], target = 9 -> [0, 1]
Code:
def twoSum(nums: List[int], target: int) -> List[int]: num_map = {} for i, num in enumerate(nums): complement = target - num if complement in num_map: return [num_map[complement], i] num_map[num] = i return []Example: [“eat”, “tea”, “tan”, “ate”, “nat”, “bat”] -> [[“eat”, “tea”, “ate”], [“tan”, “nat”], [“bat”]]
Code:
def groupAnagrams(strs: List[str]) -> List[List[str]]: anagrams = {} for s in strs: sorted_s = ''.join(sorted(s)) if sorted_s in anagrams: anagrams[sorted_s].append(s) else: anagrams[sorted_s] = [s] return list(anagrams.values())Example:
A -> B -> C -> A (cycle)A -> B -> C (no cycle)Code:
def isCyclic(V, adj): visited = [False] * V recStack = [False] * V
for node in range(V): if not visited[node]: if dfs(node, visited, recStack, adj): return True return False
def dfs(node, visited, recStack, adj): visited[node] = True recStack[node] = True
for neighbor in adj[node]: if not visited[neighbor]: if dfs(neighbor, visited, recStack, adj): return True elif recStack[neighbor]: return True recStack[node] = False return FalseExample:
LCA of 4 and 5 is 2.LCA of 4 and 6 is 1.LCA of 3 and 4 is 1.Code:
def lowestCommonAncestor(root, p, q): if not root or root == p or root == q: return root
left = lowestCommonAncestor(root.left, p, q) right = lowestCommonAncestor(root.right, p, q)
if left and right: return root return left if left else rightExample:
Input: adjList = [[2,4],[1,3],[2,4],[1,3]]Output: [[2,4],[1,3],[2,4],[1,3]]Code:
def cloneGraph(node): if not node: return None
visited = {} def dfs(original_node): if original_node in visited: return visited[original_node]
new_node = Node(original_node.val) visited[original_node] = new_node
for neighbor in original_node.neighbors: new_node.neighbors.append(dfs(neighbor)) return new_node
return dfs(node)Example:
News Feed:User A: Post 1, Post 2, Post 3User B: Post 4, Post 5User C: Post 6Code:
class NewsFeed: def __init__(self): self.posts = [] self.user_posts = {}
def create_post(self, user_id, post_id, content): if user_id not in self.user_posts: self.user_posts[user_id] = [] self.user_posts[user_id].append((post_id, content)) self.posts.append((post_id, user_id, content)) self.posts.sort(key=lambda x: x[0]) # Sort by post_id
def get_news_feed(self, user_id): user_post_ids = [p[0] for p in self.user_posts[user_id]] all_post_ids = [p[0] for p in self.posts] combined_ids = list(set(user_post_ids + all_post_ids)) combined_ids.sort(reverse=True)
feed = [] for post_id in combined_ids: for post in self.posts: if post[0] == post_id: feed.append(post) break return feed[:10] # Return top 10 postsExample:
User A sends "Hello" to User B.User B receives "Hello".User A sends "Hi" to User B.User B receives "Hi".Code:
class Messenger: def __init__(self): self.messages = {} self.users = {}
def register_user(self, user_id): if user_id not in self.users: self.users[user_id] = []
def send_message(self, sender_id, receiver_id, message): if sender_id not in self.users: self.register_user(sender_id) if receiver_id not in self.users: self.register_user(receiver_id)
self.messages[(sender_id, receiver_id)] = message self.users[receiver_id].append((sender_id, message))
def get_messages(self, user_id): if user_id not in self.users: return [] return self.users[user_id]Example:
User A uploads a story.User B sees User A's story.User A's story expires after 24 hours.User B sees User A's new story.Code:
class InstagramStories: def __init__(self): self.stories = {} self.users = {}
def upload_story(self, user_id, story_id, content): if user_id not in self.users: self.users[user_id] = [] self.stories[story_id] = (user_id, content, time.time() + 24*60*60) # 24 hours expiration self.users[user_id].append(story_id)
def get_stories(self, user_id): if user_id not in self.users: return [] current_time = time.time() return [story_id for story_id in self.users[user_id] if self.stories[story_id][2] > current_time]Move Fast
Describe a time you delivered a project under tight deadlines. How did you prioritize and execute?
Focus on Impact
Give an example of a project where your work made a measurable difference.
Be Bold
Share an example of taking a risk or trying something new. What did you learn?
Build Awesome Things
Tell me about a time you built or improved a product or feature from scratch.
DSA Mastery
Priority: Critical
Time Allocation: 50%
System/Product Design
Priority: High
Time Allocation: 20%
Meta Values & Behavioral
Priority: High
Time Allocation: 20%
Aptitude & Communication
Priority: Medium
Time Allocation: 10%
Meta’s core values are central to every interview. You must:
| Level | Experience | Base Salary | Total Package | Typical Background |
|---|---|---|---|---|
| E3 (Software Engineer) | New Grad | ₹38-48 LPA | ₹50-65 LPA | Fresh graduates, top colleges |
| E4 (SWE 2) | 2-5 years | ₹60-75 LPA | ₹80-100 LPA | 2-5 years experience |
| E5 (Senior SWE) | 5-8 years | ₹90-130 LPA | ₹1.2-1.7 Cr | Senior developers |
| E6+ | 8+ years | ₹1.7 Cr+ | ₹2.2 Cr+ | Architects, tech leads |
| Role | Level | Total Package | Requirements |
|---|---|---|---|
| Production Engineer | Entry | ₹38-55 LPA | Strong CS fundamentals |
| QA Engineer | Entry-Mid | ₹28-45 LPA | Testing, automation |
| Product Manager | Mid-Senior | ₹65-95 LPA | Product sense, tech background |
| Data Scientist | Mid | ₹55-85 LPA | ML, analytics |
Hiring Trends 2025
Increased Virtual Hiring: More online assessments and interviews System/Product Design Emphasis: More focus in interviews Diversity Hiring: Special drives for women and underrepresented groups
Process Changes
Online Assessments: More debugging and scenario-based questions Values/Behavioral Round: Mandatory for all SWE hires Faster Offers: Reduced time from interview to offer
New Initiatives
Meta Hacker Cup: Coding competition for hiring Student Programs: Internships, Meta University Internal Referrals: Strong employee referral program
Company Growth
Metaverse Expansion: More AR/VR roles in India Product Innovation: Instagram, WhatsApp, Oculus Global Mobility: Opportunities to work abroad
Ready to start your Meta preparation? Focus on DSA (especially arrays, strings, trees, graphs), system/product design basics, and Meta values. Practice mock interviews and build strong STAR stories for every value.
Pro Tip: Consistent practice on LeetCode (Meta tag) and HackerRank is key. Understand Meta’s values and be ready to demonstrate them in behavioral rounds. Every answer should show impact, learning, and boldness.
Meta placement papers are previous year question papers from Meta recruitment tests and interview rounds. These papers help students understand the exam pattern and prepare effectively.
Yes, all Meta placement papers on our website are completely free to access and download. You can practice unlimited questions without any registration or payment.
We provide Meta placement papers from recent years including 2024 and 2025. Our collection is regularly updated with the latest questions and exam patterns.
Meta placement process typically includes online assessment, technical interview, and HR interview rounds. See the placement process section for complete details.
Meta interview process typically consists of 2-3 rounds: online test, technical interview, and HR interview. Some roles may have additional rounds.
Meta eligibility criteria for freshers include minimum percentage requirements, degree requirements, and other criteria. Check the eligibility section for detailed information.
The minimum CGPA required varies by role. Check the eligibility criteria section for specific requirements.
To prepare for Meta placement: 1. Understand eligibility criteria, 2. Study exam pattern, 3. Practice previous year papers, 4. Master key skills, 5. Prepare for interviews. See the preparation strategy section for detailed guidance.
Focus on DSA (arrays, strings, trees, graphs, hash maps), system/product design (news feed, messenger, Instagram stories), Meta values (Move Fast, Focus on Impact, Be Bold, Build Awesome Things), and core computer science subjects (OS, DBMS, Networking). See the preparation strategy section for detailed topic breakdown.
Meta salary for freshers (2025): E3 (Software Engineer): ₹50-65 LPA total package (₹38-48 LPA base) for new graduates, E4 (SWE 2): ₹80-100 LPA (₹60-75 LPA base) for 2-5 years experience, E5 (Senior SWE): ₹1.2-1.7 Cr (₹90-130 LPA base) for 5-8 years. All figures are total annual compensation including base salary, bonuses, RSUs, and benefits.
Meta offers several roles for freshers: Software Engineer (E3) - most common for new graduates, Production Engineer - strong CS fundamentals required, QA Engineer - testing and automation focus, Data Scientist - ML and analytics background. E3 Software Engineer role is the primary entry-level position with ₹50-65 LPA package.
Meta offers: High compensation packages (₹50-65 LPA for freshers), work on products that impact billions (Facebook, Instagram, WhatsApp, Oculus), fast-paced, impact-driven culture, strong focus on innovation and scale, flexible working (hybrid/remote options), comprehensive health insurance, stock grants (RSUs), learning & development opportunities, fast-track promotions, global mobility opportunities, and pioneering work in metaverse and AR/VR.
Meta’s work culture is fast-paced and impact-driven. The company emphasizes “Move Fast”, “Focus on Impact”, “Be Bold”, and “Build Awesome Things”. Engineers work on products that impact billions of users. The culture values innovation, scale, and technical excellence. Work-life balance varies by team, but flexible working options are available. The company is known for its high technical bar and collaborative environment.
Meta: Focus on social media, VR, AI, strong emphasis on system/product design, Meta values (Move Fast, Focus on Impact, Be Bold), E3 package: ₹50-65 LPA, known for fast-paced culture.
Google: Focus on search, cloud, AI, strong emphasis on algorithms and system design, Google values (user focus, excellence), L3 package: ₹45-60 LPA, known for innovation.
Microsoft: Focus on cloud, enterprise software, AI, strong emphasis on problem-solving and system design, Microsoft values (growth mindset), L59 package: ₹40-55 LPA, known for work-life balance.
Choose Meta if you want fast-paced, impact-driven culture. Choose Google if you want innovation and scale. Choose Microsoft if you want work-life balance and enterprise focus.
Meta: ₹50-65 LPA (E3), social media/VR/AI focus, fast-paced culture, strong system design emphasis, Meta values-driven.
Amazon: ₹35-50 LPA (SDE I), e-commerce/cloud focus, customer obsession, strong DSA emphasis, leadership principles.
Apple: ₹40-55 LPA (ICT2), hardware/software integration, design excellence, strong problem-solving, innovation focus.
Choose Meta for social media/VR and fast-paced culture. Choose Amazon for e-commerce/cloud and customer focus. Choose Apple for hardware/software integration and design excellence.
Explore related Meta placement paper topics and preparation guides:
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Meta 2025 Papers
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Common HR questions and sample answers
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Google Placement Papers
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Amazon Placement Papers
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Microsoft Placement Papers
Problem-solving, system design, and interview experience
Ready to start your Meta preparation? Focus on DSA (especially arrays, strings, trees, graphs), system/product design basics, and Meta values. Practice mock interviews and build strong STAR stories for every value.
Pro Tip: Consistent practice on LeetCode (Meta tag) and HackerRank is key. Understand Meta’s values and be ready to demonstrate them in behavioral rounds. Every answer should show impact, learning, and boldness.
Last updated: November 2025