Nlp / Llm 应用工程师
Tasks
- Build agent capabilities
- Build automated evaluation pipelines
- Build embedding pipeline
- Create evaluation datasets
- Define evaluation metrics
- Design intent recognition
- Design prompt engineering system
- Develop semantic search
- Implement knowledge question answering
- Implement multi model routing
- Implement rag pipelines
- Manage dialogue systems
- Optimize context engineering
Perks/Benefits
- N/A
Skills/Tech-stack
Anthropic API | Chroma | DeepEval | Embeddings | Genspark | LLM APIs | Langchain | Langgraph | Llamaindex | Milvus | Model routing | Multi-model | Multi-model routing | OpenAI API | Pinecone | Prompt engineering | Promptfoo | Python | Ragas | Retrieval-Augmented Generation | TruLens | Vector Databases | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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