Build, train, deploy, and monitor ML models — plus RAG pipelines and prompt engineering.
Fetch up-to-date library documentation and code examples into Claude's context
Search and explore Hugging Face models, datasets, Spaces, and documentation
SLO design, alert optimization, dashboard generation for production systems
LLM prompt engineering — chain of thought, few-shot, system prompts, evaluation
Store and retrieve AI memories in a Qdrant vector database
RAG pipeline builder — chunking, retrieval, evaluation, vector stores
RAG system design — chunking, embedding models, retrieval strategies, evaluation
Data pipelines, ETL, warehousing, streaming architecture
Data science — statistical analysis, modeling, feature engineering, visualization
ML engineering — model training, deployment, MLOps, monitoring
Prompt engineering — crafting, testing, optimizing prompts for LLMs