岗位描述
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 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.
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技术应用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。
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。