Meta (formerly Facebook) is one of the top tech companies, known for hiring the best talent. But with thousands of applicants, how do you stand out? The key is projects. A strong portfolio with relevant projects can significantly increase your chances of getting shortlisted. In this article, we’ll explore Top 5 Projects to Get Shortlisted by Meta that showcase the skills Meta looks for. These projects cover AI, machine learning, web development and system design key areas that align with Meta’s work. Let’s dive in!
1. AI-Powered Chatbot
Why It Matters: Meta heavily invests in AI and conversational models (think Messenger chatbots and Meta AI). A chatbot project will showcase your AI, NLP (Natural Language Processing), and software development skills.
How to Build It:
- Creating an AI chatbot requires the right combination of technology, data, and strategy. Here’s a step-by-step approach:
- Define the Purpose – Identify the chatbot’s goal, whether for customer support, e-commerce, or internal automation.
- Choose the Right Platform – Platforms like Dialogflow, Microsoft Bot Framework, Rasa, or OpenAI’s GPT models offer powerful chatbot-building tools.
- Train with NLP & Machine Learning – Use pre-trained AI models and fine-tune them with business-specific data to improve accuracy.
- Integrate with Communication Channels – Deploy your chatbot on websites, messaging apps (WhatsApp, Facebook Messenger), or even voice assistants.
- Test & Optimize – Continuously monitor chatbot performance, analyze user interactions, and improve responses through iterative learning.
Pro Tip: To make your chatbot more human-like and engaging, integrate sentiment analysis. This helps the chatbot understand customer emotions and respond empathetically. Additionally, using AI-powered analytics can provide insights into customer behavior, helping businesses optimize their services further.
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2. Social Media Analytics Dashboard
Why It Matters: If you’re serious about growing your brand or business online, a Social Media Analytics Dashboard is a great changer. Instead of guessing what’s working, this dashboard gives you real-time insights into your posts, engagement, audience behavior, and overall performance.
Think of it as your social media command center, it helps you see which posts drive traffic, what content resonates with your audience, and how to tweak your strategy for maximum impact. Whether you’re a marketer, entrepreneur, or influencer, this tool saves time, improves decision-making, and boosts your online presence.
How to Build It:
Setting up a social media analytics dashboard isn’t as complicated as it sounds. Here’s how you can do it step by step:
- Choose the Right Tool – Platforms like Google Data Studio, Hootsuite, Sprout Social, or custom-built dashboards can pull data from multiple social media accounts.
- Identify Key Metrics – Track important data like engagement rates, follower growth, reach, impressions, and conversions.
- Integrate Your Accounts – Connect your Facebook, Instagram, LinkedIn, Twitter, or TikTok to centralize all insights in one place.
- Visualize the Data – Use graphs, charts, and heatmaps to make data easy to understand and actionable.
- Automate Reports – Set up scheduled reports to track performance over time without manual effort.
Pro Tip: Meta loves efficiency! Try optimizing data processing using Apache Spark or cloud services like AWS Lambda or Google Cloud Functions.
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3. Augmented Reality (AR) Filter App
Why It Matters: Meta is investing heavily in AR/VR, especially with Meta Quest and Why It Matters:
Have you ever used a fun Instagram or Snapchat filter that made you look like a cartoon character or placed virtual sunglasses on your face? That’s Augmented Reality (AR) in action! AR filter apps are changing how we interact with digital content by blending real and virtual elements seamlessly.
From social media engagement to online shopping, AR filters make experiences more interactive, immersive, and engaging. Businesses use them for brand promotions, while users enjoy them for entertainment and self-expression. The best part? AR filters are accessible to anyone with a smartphone and no fancy equipment needed!
How to Build It:
Making an AR filter app sounds complex, but with the right tools, it’s totally doable. Here’s how you can get started:
- Define Your Concept – Will your filter be fun (face masks, beauty effects) or functional (virtual try-ons, 3D objects)?
- Pick a Development Tool – Platforms like Spark AR Studio (for Facebook/Instagram), Lens Studio (Snapchat), or Unity with ARKit/ARCore make building filters easier.
- Design Your Filter – Use 3D models, animations, and effects to create eye-catching AR elements.
- Implement Face & Object Tracking – This ensures filters adjust to real-world movements naturally.
- Test and Optimize – Run multiple tests to check compatibility across devices and refine user experience.
- Publish & Promote – Once your filter is polished, submit it to platforms like Instagram, Snapchat, or your own app!
Pro Tip:
The secret to a viral AR filter is making it interactive and shareable. Add gamification elements, trendy effects, or challenges to encourage users to engage and share your filter. If you’re building for a business, ensure the filter aligns with the brand’s theme and audience interest.
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4. Full-Stack Scalable Web App
Why It Matters:
In today’s world, web apps need to be fast, scalable, and reliable to handle increasing traffic and user demands. A well-built full-stack web app ensures seamless performance, whether you’re a startup launching an MVP or a company scaling your services. Scalability isn’t just about handling more users; it’s about maintaining speed, security, and efficiency as your app grows.
How to Build It:
Creating a scalable full-stack web app involves multiple components, from front-end frameworks to database optimization. Here’s a step-by-step approach:
- Choose the Right Tech Stack – Go with popular frameworks like React, Next.js, or Vue for the front end, and Node.js, Django, or Ruby on Rails for the back end. Use SQL (PostgreSQL, MySQL) or NoSQL (MongoDB, Firebase) databases depending on your needs.
- Optimize Backend Performance – Implement efficient APIs using REST or GraphQL. Use caching mechanisms like Redis to reduce database load and improve response time.
- Scalable Hosting & Deployment – Host your app on cloud platforms like AWS, Google Cloud, or Vercel for automatic scaling. Containerization with Docker & Kubernetes ensures smooth deployments.
- Load Balancing & CDNs – Use Cloudflare or AWS CloudFront for content delivery and load balancers to distribute traffic evenly.
- Monitor & Improve – Use analytics and monitoring tools like New Relic, Prometheus, or Google Analytics to track performance and optimize accordingly.
Pro Tip:
Keep things modular and microservice-friendly. A monolithic approach may work initially, but breaking down your app into smaller, independent services allows easier scaling. Also, never underestimate the power of database indexing and query optimization to prevent bottlenecks.
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5. Recommendation System (Like Facebook’s News Feed Algorithm)
Why It Matters:
Ever wondered why your Facebook news feed, Netflix suggestions, or YouTube recommendations feel so spot-on? That’s the magic of recommendation systems! These AI-driven algorithms analyze your behavior what you like, share and engage with to show content that keeps you hooked.
For businesses, recommendation systems boost engagement, sales, and user satisfaction. They help platforms retain users by curating personalized experiences. Whether it’s suggesting products on Amazon or new songs on Spotify, this technology shapes the way we interact with digital content.
How It Works:
A recommendation system collects and processes massive amounts of data to predict what you’d like to see next. Here’s how:
- Data Collection – It tracks your interactions: clicks, likes, watch time, and searches.
- User Profiling – It builds a digital profile based on your preferences and behavior.
- Algorithm Magic – Using AI models like Collaborative Filtering, Content-Based Filtering, and Deep Learning, it finds patterns and makes predictions.
- Real-Time Updates – Your feed constantly changes based on new interactions, making recommendations smarter over time.
- Feedback Loop – The more you engage, the better the system gets at predicting your interests.
Pro Tip:
Want to build a recommendation system for your own business? Start with a mix of Collaborative Filtering (analyzing user behavior) and Content-Based Filtering (matching similar content). Use AI tools like TensorFlow, Scikit-learn, or AWS Personalize to train and optimize your model.
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Final Thoughts
Meta wants problem-solvers, not just coders. The key to standing out is not just building these projects but making them unique, optimized, and impactful. Document everything write about your approach on GitHub, Medium, or LinkedIn.
Next Steps:
- Choose one project and start coding today.
- Make it open-source and push it to GitHub.
- Share your journey on LinkedIn.
- Apply to Meta with confidence!
By working on these top 5 projects, you’ll showcase the skills that Meta looks for, making your application stand out from the crowd. Good luck!