高级Ai系统开发工程师（大模型与Rag方向）
Tasks
- Build distributed inference services with caching
- Deploy and optimize LLM and VLM models
- Design RAG system architecture
- Develop knowledge base management and multi modal retrieval optimization
- Develop scalable AI microservices
- Guide mid level engineers
- Implement quantization compression and dynamic batching
- Integrate AI services with business systems
- Integrate vector databases into RAG
- Lead technical projects and cross-team collaboration
- Manage model training deployment and monitoring pipeline
- Optimize GPU CPU heterogeneous inference
- Orchestrate agent workflows and tool calling
Perks/Benefits
- N/A
Skills/Tech-stack
Agent workflow | Distributed Systems | Dynamic batching | Elasticsearch | GPU Optimization | Go | High concurrency | Java | LLM | MCP | Message queuing | Milvus | Model Quantization | MongoDB | Multi-Modal | Multi-modal Retrieval | MySQL | Python | RAG | Redis | SGLang | SQL | Spring | Spring Boot | Spring Cloud | Spring MVC | TensorRT-LLM | Transformer | VLLM | VLM | Vector Database
Education
Roles
AI | AI Systems Engineer | Backend | Backend Engineer | Engineer | Systems Engineer
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