招聘信息分享
JOBHUNTER
聚合各大厂 / 国企官网招聘信息，实时同步官方数据
招聘信息分享
JOBHUNTER
聚合各大厂 / 国企官网招聘信息，实时同步官方数据
1.认可小米汽车品牌文化，具有创业精神; 2.高效管理门店零售团队，通过客户服务、产品知识讲解和门店推广等来驱动业务发展，对销售业绩目标负责; 3.负责计划、执行和跟进门店运营任务和项目，包括但不限于店外市场活动及销售渠道拓展活动; 4.落实公司制定的运营政策和流程满足客户需求; 5.管理、优化零售业务流程，保证客户在购买过程中的良好体验; 6.以积极正向、职业成熟的方式管理、培训和发展员工，并帮助他们达到业绩标准。
1.驱动销售目标达成:通过客户服务、产品知识讲解和推广，配合高效落实销售政策和业务流程，高效管理小组用户基盘，最大程度提升销售小组成绩，达成小组销售目标； 2.用户体验提升:通过产品讲解与试驾服务，不断提升产品体验与服务体验，创造优质的品牌;开拓更多潜在客户和产品爱好者; 3.业务拓展:配合店长有针对性地开展相关活动或合作，增加品牌曝光率; 4.活动执行:支持各类型市场活动，持续吸引与挖掘潜在用户; 5.异议解决:在客户对于产品或服务抱有疑虑时，能够有效地针对其困惑的问题提出创新性或可行性方案，尤其在财务，技术，充电，实用性，生活方式等方面； 6.数据分析:进行日常小组数据分析与复盘，配合公司政策和门店业务方向输出小组打法，提升零售流程各环节的转化效果; 7.人员业务赋能:对组员进行针对性业务辅导，提升组员销售能力，发展和培养潜在零售主管。
岗位职责： 1. 搭建并运营全球用户声音（VOC）监控体系，覆盖多渠道（客服工单、社媒、评价平台、NPS调研等），确保用户反馈实时采集与全面感知； 2. 设计全客户生命周期满意度监控和对标体系，帮助全球各区域感知产品和服务环节满意度结果并及时改善 3. 建立VOC标签体系，按产品线、问题类型、用户群体等维度分类标注，形成结构化用户洞察数据库； 4. 主导NPS（净推荐值）/NSS（净满意度）的调研设计、数据采集、分析与报告输出，跟踪核心体验指标趋势； 5. 设计体验提升机制，将VOC洞察转化为可执行的改进行动，推动产品、服务、流程的体验升级并跟踪落地效果； 6. 定期输出用户满意度与体验洞察报告，向管理层汇报全球体验状况与改进方向； 7. 与产品、研发、客服等团队紧密协作，推动用户反馈闭环，促进以用户为中心的文化落地。
岗位职责： 1. 负责海外客诉全流程管理，打通线上/线下客诉互通机制，确保多渠道客诉信息统一收集、分类处理与闭环跟踪； 2. 搭建媒体投诉与法律诉讼应对流程，制定应对策略与标准动作，协同法务、公关团队高效处置升级客诉； 3. 建立客诉标签分级体系，按严重程度、影响范围、紧急程度等维度分级管理，确保高优客诉优先处理、资源合理分配； 4. 设计客诉预防与预警机制，通过历史数据分析识别高发问题与趋势，提前制定预防措施，降低客诉发生率； 5. 统筹善意资源（补偿、关怀等）的规划与分配，制定资源使用标准与审批流程，平衡用户满意度与成本控制； 6. 定期输出客诉分析报告，提炼用户痛点与改进建议，推动产品、服务与流程的持续优化。
1、负责人才发展类（店长、管培生及平台等）培训覆盖 2、负责手机及非手机等产品知识及销售培训覆盖及检核闭环 3、负责业务支持类（对商及业务运营管理等）培训覆盖 4、拉通内外部资源，进行项目全周期管理，推动项目实施及评估闭环 5、管理区域培训团队，做好省内培训团队的人才梯队建设，建立培训在省内影响力
1. 终端测试与质量保障 负责座舱语音助手终端测试工作，主要是大控制方向，对交付质量最终负责，确保各版本/项目的测试覆盖度与通过标准，制定测试计划、用例设计、执行策略，推动缺陷收敛，把控交付质量和效率 2. 交付管理 主导测试全流程，跟踪项目里程碑，识别质量风险，及时预警并推动解决，与产品、研发、终端团队紧密协作，确保交付物满足质量要求 3. AI 赋能与效率提升 主动探索并引入大模型在测试领域的应用，如用例生成、自动化脚本编写、缺陷分析、测试数据构造等，建设 AI 辅助测试工具链，提升团队整体测试效率，并关注前沿技术动态，持续探索 AI 在质量保障场景的落地可能性
1.聚焦车载车控 / 导航 / 语音业务，兼顾业务质量交付与测试技术建设，足够胜任测试平台与工具的开发。 2.参与车载项目全流程质量管控，完成需求评审、测试方案、风险识别、问题闭环，保障版本交付质量。 3.主导车载自动化测试平台、场景仿真、专项测试框架的架构设计与核心开发，搭建可复用可扩展的测试技术体系，提升自动化覆盖率。 4.结合大模型 / AI 技术落地测试场景，开发 AI 辅助测试能力，实现测试提效。 沉淀测试规范方法论，推进测试左移，赋能团队。
1.AI 赋能战略规划与落地推进：聚焦 AI + 材料、AI + 汽车等核心赛道，制定技术赋能路线图与关键里程碑，推动 LLM、AI Agent 等前沿技术从能力验证走向规模化业务落地，实现可量化的价值交付 2.技术价值叙事与生态影响力建设：将团队技术突破转化为业务方可感知的价值语言，打造标杆用户案例，策划技术分享与成果展示，拓展集团内外种子用户并推动产品规模化采纳 3.产品全生命周期管理与用户成功体系搭建：主导 AI 产品从 0 到 1 的完整生命周期，识别冷启动关键卡点并推动持续迭代，确保技术成果落地为用户可用、好用的产品能力 4.跨团队协同与研发节奏管理：对齐算法、工程与业务团队的技术愿景，拆解攻坚任务、协调内外部资源，破解跨域协作瓶颈，保障创新项目按计划从原型验证走向工程化交付 5.价值度量与知识沉淀：建立 AI 赋能成效的量化评估体系，定期输出进展复盘与价值报告，推动项目经验与方法论的标准化沉淀，实现成效可追踪、可复用、可传播
Job Description 1. Achieve regional sales targets for ST and SO 2. Drive product coverage across retail outlets 3. Manage inventory and PSI 4. Manage and optimize retail presence 5. Drive sales performance of key partner and stores 6. Oversee the recruitment, management, and sales performance of the promoter team 7. Maintain strong relationships with key regional stakeholders
负责项目组测试实施，测试工具维护，问题跟踪闭环等工作： 1.参与产品需求评审完成测试用例设计及用例评审； 2.根据产品需求完成测试执行工作，积极推动问题解决及闭环； 3.独立完成产品的回归测试以及需求兼容性测试； 4.根据业务现状设计发散性测试用例，满足业务要求； 5.总结测试任务，根据缺陷情况对产品质量做出预判和汇报； 6.升级维护测试工具，完成提效小工具研发； 7.参与 AI Native 软件工程体系建设，探索大模型、Agent、多模态等技术在软件测试中的落地应用。
1. 了解AI测试，熟悉使用主流AI编程工具如ClaudeCode/Codex进行Agent开发和调试。 2. 熟练使用Java&python&sh等语言进行自动化代码编写，掌握Uiautomator2.0、Pytest、Junit测试框架；主导自动化测试框架搭建熟练使用adb相关命令。 3. 负责小米Android端自动化测试工作，能够独立完成测试用例的设计、执行，及时跟进项目相关Bug，并及时推动问题解决，跟进软件质量；持续优化测试脚本，提升测试执行效率与稳定性，将自动化测试全面融入持续集成 / 持续交付（CI/CD）流程，加速产品迭代。 4. 挖掘团队测试痛点，自主开发实用测试工具，如数据生成工具、缺陷管理辅助工具等；参与测试平台建设，实现测试用例管理、测试结果分析可视化，提升测试流程管理效率。独立负责自动化测试方案设计，按照标准流程完成测试工作。 5. 高效运用 JIRA 等缺陷管理工具，详细记录、跟踪产品缺陷，与开发团队密切沟通，推动问题及时解决，确保产品上线前缺陷收敛至可控范围。 6. 关注行业测试技术发展趋势，积极引入新技术、新方法，定期组织团队内部技术分享与交流，提升整体技术水平。
1、撰写&拍摄文化内容：文笔好、能独立撰写稿件；会拍摄剪辑、能制作有质感有网感的活动视频。多形式宣贯文化，运营文化专栏。 2、参与组织文化活动：有创意，有执行力，参与策划有趣、有参与度的文化活动；有责任心、靠谱尽责，全程支持文化活动落地。 3、协同意识强，机动支持部门其他工作。
1. 协助部门日常行政事务开展，落实员工办公体验一应事宜对接处理； 2. 包含协助接待访客、会议支持、包含参会人邀约、会议现场布场； 3. 协助部门团建、节日活动、生日会、员工福利的策划及组织落地，包含活动场地协调布场、采购物资； 4. 支持部门资料文件的整理、归档；
- Serve as the primary compliance subject matter expert on critical projects (e.g., data security, cross-border data transfer compliance, personal data protection), ensuring security and data protection requirements are embedded by design. - Collaborate closely with engineering, product, legal, and DevOps teams to guide the implementation of compliant technical solutions throughout the entire data lifecycle. - Develop, maintain, and improve information security policies, standards, procedures, and guidelines. - Lead and perform internal risk assessments across multiple frameworks, including ISO/IEC 27001/27701, GDPR, SOC2, PCI DSS and other relevant standards. - Lead the end-to-end lifecycle of cybersecurity risk remediation activities, ensuring identified risks are effectively mitigated within agreed timelines. - Manage international security operations, incident response, and regional liaison to adapt global strategies to local needs. - Provide security architecture governance and oversight for new and existing technology solutions.
- Manage the full lifecycle of core security solutions (WAF, MiShield, HIDS) for Xiaomi’s international business, including configuring policies, optimizing rules, and expanding coverage to protect web and mobile applications against threats such as OWASP Top 10 - Develop real-time monitoring and alerting frameworks to analyze security logs, detect anomalous traffic and attacks, produce root-cause analysis reports, and improve defense strategies - Contribute to the design and implementation of an API security framework for international operations, creating models for abnormal behavior detection and access control to prevent unauthorized data access and API abuse - Integrate API security with gateways and microservices, incorporate SAST/DAST tools to promote shift-left security practices, and establish developer security guidelines - Oversee vulnerability management processes including scanning, risk assessment, and remediation for international business, implementing high-risk vulnerability response mechanisms and collaborating with R&D teams on code-level fixes - Monitor global threat intelligence and zero-day vulnerabilities, organize red/blue team exercises, and refine emergency response protocols - Ensure security operations comply with regional regulations such as GDPR and Singapore PDPA, preparing compliance audit reports - Collaborate with international business units, local compliance teams, and third-party vendors to provide security technical support and training
1. Support the operation, maintenance, and development of the company’s overseas data warehouse (mobile device, IoT, and app data domains) 2. Develop and implement data processing techniques and analytics applications to transform raw data into meaningful insights 3. Build and maintain ETL/ELT pipelines using data-oriented programming languages (e.g., Python, SQL) 4. Apply basic data modeling and data mining techniques to process structured and semi-structured datasets 5. Assist in analyzing large datasets and generating insights to support overseas business operations 6. Create data visualizations and simple reports using BI or visualization tools (e.g., Tableau, Power BI, or similar) 7. Collaborate with cross-functional teams to understand data requirements and support analytics use cases 8. Participate in testing, deployment, and monitoring of data workflows
1. Support the daily operation of cloud infrastructure and production systems to help ensure service availability, stability, and performance. 2. Monitor production systems, assist in troubleshooting incidents, and perform routine operational tasks under the guidance of senior engineers. 3. Assist in deploying, configuring, maintaining, and optimizing cloud infrastructure, Linux servers, and containerized applications in accordance with operational best practices. 4. Participate in production changes, system upgrades, routine maintenance, and on-call rotations after successfully completing the required onboarding and training program. Compensatory time off will be provided in accordance with company policy. 5. Learn and contribute to automation initiatives through scripting, operational tools, and AI-assisted engineering workflows to improve operational efficiency and reduce manual effort. 6. Collaborate with software engineers, infrastructure teams, and other stakeholders to resolve technical issues, improve system reliability, and continuously develop technical knowledge and engineering skills.
1. Learn to research, design, and develop software and utility programs for managing large-scale distributed database and storage systems, with support from the team. 2. Assist in analysing user and system requirements, and contribute to software solutions by applying computer science and engineering fundamentals. 3. Help update and enhance existing software capabilities, and participate in software testing and validation for database and storage services. 4. Collaborate with engineers across different teams to support the integration of database systems, and gradually contribute to system specifications and performance requirements. 5. Under the guidance of a mentor, build tooling and automation for monitoring, capacity planning, backup, and incident response. 6. Progressively participate in on-call rotations and production incident remediation after completing onboarding and training.
1. Support the daily operation of cloud infrastructure and production systems to help ensure service availability, stability, and performance. 2. Monitor production systems, assist in troubleshooting incidents, and perform routine operational tasks under the guidance of senior engineers. 3. Assist in deploying, configuring, maintaining, and optimizing cloud infrastructure, Linux servers, and containerized applications in accordance with operational best practices. 4. Participate in production changes, system upgrades, routine maintenance, and on-call rotations after successfully completing the required onboarding and training program. Compensatory time off will be provided in accordance with company policy. 5. Learn and contribute to automation initiatives through scripting, operational tools, and AI-assisted engineering workflows to improve operational efficiency and reduce manual effort. 6. Collaborate with software engineers, infrastructure teams, and other stakeholders to resolve technical issues, improve system reliability, and continuously develop technical knowledge and engineering skills.
1. 负责各类LLM/VLM的预训练，后训练，并应用于实际业务中 2. 探索Agent记忆系统，包括参数化记忆与更新，记忆自进化，连续学习，个性化大模型等方向，通过全生命周期个人数据提升大模型的个性化生成与决策能力 3. 融合多模态数据，攻关持续在线的连续感知-记忆-决策Agent框架，推动个性化主动服务的前沿研究 4. 探索机器学习领域的新技术，探索与其他领域的技术融合。发表高水平论文和专利