AI Agent研发工程师

该职位来源于猎聘 岗位职麦 I Job Responsibilities -参与制造场景 AI Agent 架构设计、模型研发与原型开发，重点适配设备生产、产线管控、质检运维等场景，实现 AI Agent 对生产全流程的智能协同与调度。 Participate in architectural design, model R&D and prototype development of manufacturing-oriented AI Agents, focusing on equipment manufacturing, production line management, quality inspection and equipment maintenance scenarios, to realize intelligent collaboration and scheduling of full production workflows powered by AI Agents. -协助开展设备生产仿真工作，搭建设备运行、产线流转、工艺执行相关仿真模型，完成仿真试验、参数调试与优化，支撑生产工艺升级与设备效能提升。

Assist in equipment production simulation, build simulation models covering equipment operation, production line logistics and process execution, conduct simulation tests as well as parameter tuning and optimization to support production process upgrading and equipment efficiency improvement. -参与 RAG 知识库搭建与优化，梳理轴承加工制造、设备运维、AI 技术应用等相关知识，构建适配工业场景的知识库，支撑 AI Agent 智能问答、决策辅助功能落地。 Take part in the construction and iteration of RAG knowledge base; organize domain knowledge including bearing machining & manufacturing, equipment maintenance and AI industrial application, build industry-specific knowledge base to enable intelligent Q&A and decision-aiding functions of AI Agents. -配合团队开展 AI 参数优化与 3D 模型生成相关工作，利用 AI 技术优化设备生产参数、零部件 3D 建模参数，辅助完成零部件 3D 模型智能生成、优化与验证。

Cooperate with the R&D team on AI parameter optimization and intelligent 3D model generation; leverage AI algorithms to optimize production parameters and part 3D modeling parameters, and assist in automatic generation, optimization and verification of component 3D models. -跟进制造业智能化需求，参与需求调研、方案梳理，将汽车零部件生产、设备运维等业务痛点，转化为设备生产仿真、AI Agent、RAG 知识库、AI 参数 / 3D 生成的技术实现路径。 Collect and analyze intelligent upgrading demands from manufacturing business; conduct requirement research and solution arrangement, translate practical pain points in auto parts production and equipment maintenance into actionable technical solutions covering production simulation, AI Agent, RAG knowledge base, AI parameter tuning and intelligent 3D generation. -配合研发团队完成算法调研、技术预研、文献梳理、原型 demo 搭建，逐步沉淀设备生产仿真、AI Agent 开发、RAG 应用、AI 参数与 3D 生成相关技术能力。

Support the R&D team in algorithm investigation, advanced technology pre-research, literature review and prototype demo development, and accumulate core technical know-how in production simulation, AI Agent development, RAG implementation, AI parameter optimization and intelligent 3D modeling. -参与 MES/QMS/WMS/EMS 等工业系统与 AI Agent、RAG 知识库的对接适配，协助完成联调测试及应用试点落地，支撑设备生产、轴承及零部件制造智能化升级。 Participate in interface development and adaptation between industrial systems (MES/QMS/WMS/EMS) and AI Agent & RAG knowledge base; assist in joint debugging, testing and pilot implementation to drive intelligent transformation of bearing and auto component manufacturing. -跟踪 AI 大模型、AI Agent、RAG 技术、工业仿真、3D 智能建模前沿动态，开展技术储备与课题研究，形成技术文档、专利、软著等成果。

Keep track of cutting-edge progress of large language models, AI Agent, RAG, industrial simulation and AI-driven 3D modeling; carry out technical research and project studies, and deliver outcomes including technical specifications, invention patents and software copyrights. -协同生产工厂，参与设备智能化改造、AI 技术落地项目的技术支撑与方案研讨。 Collaborate with on-site production plants to provide technical support and participate in solution discussion for equipment intelligent retrofitting and AI industrialization projects. 任职要求 | Job Requirements 1. 学历要求 | Educational Background 硕士及以上学历，应届毕业生或毕业不久的优秀研究生均可投递。 Fresh graduates or outstanding graduate students who have just graduated are eligible to apply. 2. 专业背景 | Academic Major 人工智能、计算机科学与技术、软件工程、自动化、控制工程、机电一体化、机械工程、车辆工程、汽车零部件等相关工科专业。 Majors in Artificial Intelligence, Computer Science and Technology, Software Engineering, Automation, Control Engineering, Mechatronics, Mechanical Engineering, Vehicle Engineering, Auto Parts and other related engineering disciplines. 3. 研究方向匹配 | Research Direction Matching 研究生研究方向、毕业设计或课题涉及以下任意领域即可：AI算法、AI智能体（AI Agent）、大模型应用、RAG知识库、工业仿真、设备生产仿真、3D建模、参数优化等，无需全部掌握。 Candidates whose postgraduate research directions, graduation projects or topics involve any of the following fields are qualified: AI algorithms, AI Agent, large model application, RAG knowledge base, industrial simulation, equipment production simulation, 3D modeling, parameter optimization, etc. Full proficiency in all fields is not required. 4. 专业基础能力 | Professional Competencies 具备扎实的工科科研思维与逻辑能力；熟练掌握Python、Java、C++等任意一门主流开发语言；具备算法建模、仿真建模、程序开发、知识库搭建、3D建模中任意一项及以上基础能力即可。 Solid engineering scientific research thinking and logical thinking ability; proficient in at least one mainstream development language such as Python, Java, C++; have basic capabilities in any one or more of algorithm modeling, simulation modeling, program development, knowledge base construction and 3D modeling. 5. 学习能力与发展意愿 | Learning Ability & Development Willingness 愿意深耕汽车零部件（轴承行业）、高端制造工业场景；对设备生产仿真、AI Agent、RAG知识库、AI参数优化、3D智能生成等技术方向具备浓厚兴趣；认同企业培养模式，能够接受公司定向培养与一对一导师带教，主动在项目实践中迭代提升技术能力。 Willing to devote oneself to the industrial scenarios of auto parts (bearing industry) and high-end manufacturing; have a strong interest in equipment production simulation, AI Agent, RAG knowledge base, AI parameter optimization, 3D intelligent generation and other technical directions; recognize the company’s training model, accept targeted cultivation and one-on-one mentor guidance, and take the initiative to improve technical capabilities in project practice. 6. 经验要求 | Work Experience 无硬性成熟工程项目经验要求。无需独立完成过设备生产仿真、AI Agent开发、RAG知识库搭建、AI 3D生成等落地项目，只要专业对口、研究方向契合、愿意持续学习深耕即可。 No mandatory requirements for mature engineering project experience. Candidates do not need to have independently completed practical projects such as equipment production simulation, AI Agent development, RAG knowledge base construction and AI 3D generation. Only matching major, consistent research direction and willingness to keep learning and in-depth cultivation are required. 7. 综合素质 | Comprehensive Literacy 逻辑思维清晰，具备优秀的技术预研能力；拥有良好的沟通表达与团队协作能力，可高效配合跨专业团队开展联合研发；具备基础的问题分析、拆解与落地解决能力。 Clear logical thinking and excellent technical pre-research ability; good communication, expression and teamwork skills, able to efficiently cooperate with cross-disciplinary teams for joint R&D; possess basic capabilities of problem analysis, decomposition and practical solving. 职业发展意愿 | Career Intention 愿意长期扎根制造业数字化、工业人工智能、智能仿真核心赛道，认同企业阶梯式培养模式，愿意从技术预研、原型开发、项目试点应用等基础工作起步，持续沉淀工业场景技术经验，逐步成长为企业核心技术骨干。 Willing to take root in the core tracks of manufacturing digitalization, industrial artificial intelligence and intelligent simulation for a long term, recognize the company’s step-by-step training model, start from basic work such as technical pre-research, prototype development and project pilot application, continuously accumulate technical experience in industrial scenarios, and gradually grow into the company’s core technical backbones.