RAG Clinical Question Answering
RAG pipeline with LangChain and ChromaDB for clinical question answering, including hybrid search (BM25 + dense) and Reciprocal Rank Fusion.
- Python
- LangChain
- ChromaDB
- FastAPI
- Docker
- RAG
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AI / ML
AI / ML Engineer
Models, evaluation, and inference systems you can operate.
Work in this track focuses on supervised learning, computer vision, recommenders, and MLOps — training, tracking, and serving models from repositories that actually exist on GitHub.
Skills evidenced in repositories
Languages
- Python
- SQL
Machine learning
- Scikit-learn
- XGBoost
- PyTorch
- TensorFlow
- Keras
Computer vision
- YOLOv8
- OpenCV
- CNN
- Grad-CAM
MLOps
- MLflow
- DVC
- FastAPI
- Docker
- GitHub Actions
Projects for this role
11 repositories mapped from the shared project catalogue.
Multi-Agent Research Assistant
LangGraph multi-agent workflow with planner, researcher, writer, and evaluator agents that produce cited research reports.
- Python
- LangGraph
- LangChain
- OpenAI
- FastAPI
Product Recommender with FAISS
Hybrid product recommender combining collaborative filtering with embedding similarity search in FAISS.
- Python
- PyTorch
- Sentence Transformers
- FAISS
- FastAPI
- Docker
Domain LLM Fine-Tuning with LoRA
Domain-specific LLM fine-tuning with LoRA, comparing the adapted model against the base model on a fixed evaluation set.
- Python
- PyTorch
- Hugging Face
- LoRA
- PEFT