Nlp / Llm 应用工程师
Tasks
- Build agent model capability layer
- Build automated evaluation pipeline
- Build embedding pipeline
- Create agent evaluation dataset
- Define evaluation metrics
- Design intent recognition for agents
- Design prompt engineering framework
- Develop knowledge question answering
- Develop semantic retrieval for knowledge base
- Evaluate model quality and inference cost
- Implement RAG retrieval augmented generation
- Implement dialogue management
- Implement multi model routing strategy
- Optimize context engineering
Perks/Benefits
- N/A
Skills/Tech-stack
Agent | Anthropic API | Chroma | Context engineering | DeepEval | Dialogue Management | Embedding | Evaluation | Intent Recognition | Langchain | Langgraph | Llamaindex | Milvus | Model routing | Multi-model | Multi-model routing | OpenAI API | Pinecone | Promptfoo | Python | RAG | Ragas | TruLens | Vector Database | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | LLM Engineer | NLP Engineer
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