nlp-engineering - Build NLP Pipelines and Semantic Search
Build NLP pipelines for preprocessing, tokenization, embeddings, semantic search, classification, named entity recognition, summarization, and RAG chunking.
Tags
Updated: 2026-10-03Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Clean and normalize text
- Tokenize text
- Generate text embeddings
- Build semantic search
- Classify text categories
- Extract named entities
- Summarize documents
- Chunk documents for RAG
- Tune tokenization strategies
- Evaluate NLP systems
Inputs
- Raw text
- Documents
- Search queries
- Training datasets
- Evaluation datasets
- Text labels
- Tokenization configurations
- Model checkpoints
Outputs
- Cleaned text
- Text embeddings
- Semantic search results
- Classification labels
- Named entities
- Document summaries
- RAG document chunks
- Evaluation metrics
- NLP implementation guidance
Requirements
- Claude Code, Gemini CLI, or OpenAI Codex