机器人交互工程师-擎天租子公司
Tasks
- Add exception handling and fallback
- Analyze bad cases and improve models
- Build structured memory and state machine task orchestration
- Deploy solutions to business scenarios
- Design and develop LLM agent applications
- Develop RAG pipelines
- Develop multi agent collaboration mechanisms
- Implement agent runtime and session context
- Implement document parsing and text chunking
- Implement hallucination defense
- Implement reranking and answer generation
- Implement task routing and task decomposition
- Integrate tool calling and result aggregation
- Manage prompt versions and structured output
- Optimize cost and response latency
- Perform vectorization and hybrid retrieval
- Research and validate new LLM agent technologies
- Set up offline evaluation and online metrics
Perks/Benefits
- N/A
Skills/Tech-stack
ASR | Agent systems | Elasticsearch | Function Calling | HTTP | Java | LangChain4J | Langchain | Langgraph | Message queuing | Milvus | Multi-Agent | Multi-Agent Systems | Multi-Modal | Multi-modal processing | MySQL | Plan-and-Execute | Prompt engineering | Qdrant | React | Redis | Retrieval-Augmented Generation | SGLang | Spring AI | Spring Boot | State Machine | Structured Output | TTS | Unit Testing | VLLM | VLM | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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