class FadiFares:
name = "Fadi Fares"
role = "Software & AI Engineer"
expertise = [
"Machine Learning & Deep Learning",
"Generative AI & LLMs",
"AI Agents & Multi-Agent Systems",
"Full-Stack AI Applications",
]
currently = "Building production-grade AI systems"
philosophy = "AI should solve real problems, not just demo well."
def greet(self):
return "Let's build something intelligent. 🚀"
|
Autonomous multi-agent systems using LangGraph & LangChain — RAG pipelines, tool-use, memory, and orchestration. |
Fine-tuning, prompt engineering, and deploying large language models into scalable production APIs. |
End-to-end applications — FastAPI backends, Flutter mobile frontends, Firebase real-time sync, and vector search with Qdrant. |
|
Production RAG pipelines with semantic search, hybrid retrieval, re-ranking, and Qdrant vector stores. |
CNNs, Transformers, and custom architectures in PyTorch and TensorFlow for vision, NLP, and tabular tasks. |
Containerized ML services with Docker, CI/CD via GitHub Actions, and scalable inference endpoints. |