职位介绍： 作为质量数字化团队核心成员，承接工厂质量保证条线数字化与智能化目标。致力于应用数字思维和智能工具为质量部下辖团队革新生产力工具，链接质量上下游团队打造覆盖产品全生命周期、全业务链的质量数字生态，用数据驱动质量改进与降本增效决策。 岗位职责： Contribute to quality digital strategy and priority programs; deliver forward-looking, innovation-led, data-driven digital solutions. Deep-dive quality operations; analyze manufacturing, equipment, and vehicle data; proactively identify high-value use cases and co-design business solutions; own data- and algorithm-layer delivery. Use analytics to lift first-pass yield and reduce scrap, rework, and quality loss. Productize reusable tools and Agent suites for high-repeat / complex workflows; orchestrate multi-agent systems (MAS) for end-to-end business-chain automation and ensure correct, high-adoption use by the business. Drive high-value quality AI use-case discovery and pilots (e.g., visual inspection, anomaly alerting, defect root-cause assist); own evaluation, usage standards, and scale-out. Land at least one AI project per year with quantified business value. Grow into a deep-learning specialist in at least one domain and independently lead machine-vision inspection, time-series diagnostics, anomaly detection, or optimization algorithms; solve data scarcity, label noise, and false-positive / false-negative issues in production. Maintain existing data pipelines and visualization dashboards; support business data needs with accuracy and completeness. Lead quality data governance and deliver business-aligned, implementable governance solutions. 参与质量数字化战略规划与重点项目实施，应用前瞻性、创新型视野提供技术和数据驱动的数字化解决方案。 深入理解质量业务内容，分析制造、设备和车辆数据，主动识别高价值场景并协同策划业务解决方案，主导项目在数据和算法层的落地；通过数据分析支撑一次通过率提升、降低报废返工与质量损失等降本增效目标。 围绕高重复性需求/复杂业务场景沉淀并开发可复用工具与 Agent 套件；具备多智能体系统编排能力，为业务链提供端到端智能体自动化工具，并确保业务端高效、正确使用。 推动质量领域 AI 高价值场景识别与试点验证（如视觉检测、异常预警、缺陷根因辅助分析等），参与效果评估、使用规范建立及规模化推广，每年至少参与 1 项可量化价值的 AI 项目落地。 愿意在至少一个深度学习方向成长为资深专家，逐步具备独立主导机器视觉检测、时序信号诊断、异常检测或优化算法落地的能力，能解决数据稀缺、标签噪声及误报漏报等工程难点。 维护现有数据管道和数据可视化看板，支持业务数据需求，确保数据准确性、完整性。 牵头质量数据治理工作，贴合业务需求提供落地的数据治理方案。 遵守公司规章制度，积极查找并汇报隐患/事故，提出安全建议，通过持续改进创造安全环境。践行“安全第一，人人有责”，“眼见，发声，行动”的安全文化。 任职要求： Bachelor’s or above in Statistics, Mathematics, Data Science, Computer Science, or a related STEM field. Strong SQL and Python for data processing, analysis, and productionizing data workflows. Solid depth in at least one deep-learning domain (computer vision, time-series diagnostics, anomaly detection, or optimization algorithms). Rigorous logical thinking and strong problem-solving skills. Strong communication skills; translate data analysis conclusions accurately to business stakeholders and help non-technical colleagues quickly understand insights. Comfortable multitasking in a fast-paced, results-driven environment. Fluent spoken and written Chinese and English. Hands-on experience building AI Agents and multi-agent orchestration (MAS), with production delivery preferred; exposure to LLM applications, RAG/knowledge workflows, and cross-functional AI enablement is a plus. Awards in math or programming contests (domestic or international) preferred. 2027应届毕业生，毕业时间在2026年11月至2027年10月毕业的海内外学生，统招本科及以上学历； 本科及以上学历，统计学、数学、数据科学、计算机或其他理工科专业。 熟练使用 SQL、Python 等语言处理与分析数据。 具备缜密的逻辑思维和优秀的问题分析能力。 具备良好的沟通表达能力，能将数据分析结论准确传达给业务同事，帮助无技术背景同事快速理解。 具备较强的多任务处理能力和抗压能力，能适应快节奏、以结果为导向的工作环境。 在至少一个深度学习方向具备扎实知识。 流利的中英文听说读写能力。 具备 Agent 和 MAS（多智能体系统）开发能力和项目经验优先。 获得国内外数学竞赛，计算机竞赛奖项者优先。