聚焦制造业研发/工程/生产/供应链/质量等部门业务场景，基于主流大模型工具，导入并适配各部门的AI应用工具或自动化流程。 / Focus on business scenarios of core departments such as R&D, IE, Production, SCM and Quality in manufacturing sector, and introduce and develop AI application tools or automated processes suitable for each department based on mainstream large language models (LLMs).

•Focus on business scenarios across SCM, RD, IE, Production, and Quality in manufacturing sector. Based on mainstream large models, participate in building AI applications under the application-layer core framework: Agent + RAG + + ToolChain.聚焦家电制造供应链、研发、工业工程、生产、质量等部门业务场景，基于主流大模型，参与构建以 智能体 + RAG + 工具链为应用层核心框架的 AI 应用。
•Assist in the design, development, and debugging of RAG system, including document parsing, vector database construction, retrieval strategy optimization, and prompt tuning for question answering.协助 RAG 系统 的设计、开发与调试，包括文档解析、向量库构建、检索策略优化、问答 Prompt 调优。
•Participate in the design and implementation of AI Agent, including tool selection, tool calling logic, task planning, memory management, and multi-step reasoning process optimization.参与 AI 智能体（Agent） 的设计与实现，包括工具选择、工具调用逻辑、任务规划、记忆管理与多步推理流程优化。
•Conduct verification and effect optimization for Agent reasoning, RAG retrieval accuracy, memory persistence, and Tool Chain execution.对智能体推理效果、RAG 检索准确率、记忆持久化、工具链执行进行验证与效果优化。
•Collect departmental requirements, combine with manufacturing business rules, design and implement AI automation processes.收集各部门 AI 应用需求，结合家电制造业务规则，设计并落地 AI 自动化流程。
•Assist in building test cases, output evaluation reports, and promote AI system landing in multiple departments.协助构建测试用例、输出评测报告，推动 AI 系统在多部门落地

Job Requirements
岗位要求
•本科及以上学历，计算机、软件工程、自动化、数据科学等相关专业，具备一定的编程基础。 / Bachelor's degree or above, major in Computer Science, Software Engineering, Automation, Data Science or related fields, with certain programming foundation.
•Familiar with Python; understand LLM API (DeepSeek, OpenAI, etc.).熟悉 Python，了解主流大模型 API 调用。
•Understand and have hands-on experience with RAG: familiar with document splitting, embedding, vector database, retrieval & generation process.了解并实践过 RAG：熟悉文档切分、Embedding、向量库、检索增强生成流程。
•Understand the basic principles of AI Agent: understand tool calling, task planning, reasoning, memory mechanism.理解 AI Agent 基本原理：了解工具调用、任务规划、推理、记忆机制。
•Master basic prompt engineering; able to optimize Agent behavior and RAG output quality.掌握基础提示词工程，能优化智能体行为与 RAG 回答质量。

实习时长
Internship Duration
3个月及以上，每周到岗≥3天
At least 3 months, on-site work ≥ 3 days per week