A portfolio-ready GitHub profile with 3–5 deployed projects, a clean README, and LinkedIn presence gets you shortlisted. This guide shows exactly how.
Tick off each item. Recruiters look for these specifically when screening AI/ML profiles.
Create a file at github.com/YOUR-USERNAME/YOUR-USERNAME/blob/main/README.md (special repo with same name as your username).
# Hi, I'm [Your Name] 👋 🎓 B.Tech CSE | Final Year | [College Name] 🤖 Building AI/ML systems — LLMs, RAG, Computer Vision 💼 Actively seeking ML Engineer / AI Engineer roles (2025) 📍 [City, India] --- ## 🛠 Tech Stack **Languages:** Python · SQL · JavaScript **ML/DL:** scikit-learn · PyTorch · TensorFlow · HuggingFace **LLM/GenAI:** LangChain · OpenAI API · ChromaDB · LlamaIndex **MLOps:** Docker · GitHub Actions · MLflow · FastAPI **Data:** pandas · NumPy · matplotlib · plotly · Streamlit --- ## 🚀 Featured Projects | Project | Description | Tech | Demo | |---|---|---|---| | [Document Q&A Assistant](link) | RAG chatbot for PDF documents | FastAPI · ChromaDB · OpenAI | [Live Demo](link) | | [Inventory Forecasting Dashboard](link) | ARIMA + Prophet time series forecast | Streamlit · Prophet | [Live Demo](link) | | [AI Resume Screener](link) | LLM-based resume scoring system | OpenAI · PyMuPDF | [Live Demo](link) | --- ## 📊 GitHub Stats  --- ## 📫 Let's Connect [](https://linkedin.com/in/YOUR-PROFILE) [](https://huggingface.co/YOUR-USERNAME) [](https://kaggle.com/YOUR-USERNAME) 💬 Open to internships, full-time roles, and research collaborations in AI/ML.
Every project repo needs a README that answers: what it does, how to run it, what it uses, and where to see it live.
# Project Name > One-line description: what it does and who it's for. [](https://YOUR-DEMO-URL) [](https://python.org) [](LICENSE) --- ## 🎯 What This Project Does 2–3 sentences explaining the problem it solves and the approach used. **Example:** This RAG-based chatbot lets users upload PDF documents and ask questions in natural language. It uses ChromaDB for vector storage and gpt-4o-mini for generating grounded answers. --- ## 🏗 Architecture ``` User Input → Text Extraction → Embedding → Vector DB → LLM → Answer ``` *(Replace with your actual architecture diagram or Mermaid chart)* --- ## ✨ Features - Feature 1 — what it does - Feature 2 — what it does - Feature 3 — what it does --- ## 🛠 Tech Stack | Component | Technology | |---|---| | Backend | FastAPI / Streamlit | | LLM | OpenAI gpt-4o-mini | | Vector DB | ChromaDB | | Deployment | Render.com | --- ## 🚀 Quick Start ```bash git clone https://github.com/YOUR-USERNAME/PROJECT-NAME cd PROJECT-NAME python -m venv .venv && source .venv/bin/activate pip install -r requirements.txt cp .env.example .env # fill in your API keys python app.py # or: streamlit run app.py ``` --- ## 📸 Screenshots | Home Page | Results | |---|---| |  |  | --- ## 📁 Project Structure ``` project/ ├── app.py # Main application ├── core/ # Business logic ├── requirements.txt ├── .env.example └── README.md ``` --- ## 🎓 Viva-Ready Built as part of final-year project. Architecture decisions explained in [architecture.md](docs/architecture.md). --- ## 📜 License MIT — free to use and modify for learning purposes.
GitHub renders Mermaid diagrams automatically in README.md files — no image upload needed.
```mermaid
flowchart LR
A[📄 PDF Upload] --> B[Text Extraction\nPyMuPDF]
B --> C[Chunking\n500 tokens, 50 overlap]
C --> D[Embeddings\ntext-embedding-3-small]
D --> E[(Vector DB\nChromaDB)]
F[❓ User Question] --> G[Query Embedding]
G --> E
E -->|Top 5 chunks| H[LLM Prompt\ngpt-4o-mini]
H --> I[✅ Grounded Answer]
```
A live URL is non-negotiable for a strong portfolio. These three platforms are free and take under 10 minutes to set up.
Best for: FastAPI, Flask, Streamlit, any Python web app. Sleeps after 15 min inactivity on free tier (wakes in ~30s).
requirements.txt with all dependencies to your repoProcfile: web: uvicorn app:app --host 0.0.0.0 --port $PORTgit push origin mainyour-app.onrender.com URL in ~3 minutesBest for: Streamlit apps only. One-click deploy directly from GitHub. No sleep on free tier for public apps.
app.py)your-app.streamlit.app in ~2 minutesBest for: ML demos with GPU (image models, LLMs, audio). Free T4 GPU available. Gradio or Streamlit SDK.
git clone https://huggingface.co/spaces/USERNAME/SPACE-NAMEapp.py, requirements.txt)git add . && git commit -m "deploy" && git pushhuggingface.co/spaces/USERNAME/SPACE-NAMEBest for: databases + backend APIs. $5 free credit per month. Supports PostgreSQL, Redis, any Dockerfile.
Recruiters spend an average of 7 seconds on a profile. These changes maximise what they see in that time.
Example (Final year):
Example (Fresher):
The LinkedIn Featured section shows below your headline. Use it to directly link your 3 best projects.
Follow 20–30 AI/ML companies and leaders. Like and comment on their posts about AI trends. LinkedIn's algorithm will surface your profile to more recruiters in those companies. Takes 10 minutes per week.