
同程旅行开发支持
任职要求
任职要求: 1、具备较为成熟的招商、物业中介、酒店开发等工作经验,有成功签约酒店项目者优先、带项目入职者可匹配更…
工作职责
工作职责: 1、在规定期限内完成个人开发酒店签约指标。 2、寻找物业信息,包括物业的地理位置、周边市场条件、建筑结构、面积、改造条件、业主情况、产权情况、并调研周边酒店房价、出租率等经营信息。 3、负责与业主和和投资人谈判,把控物业租金,寻找并匹配合适的投资人,能积极协调项目设计,经营考察和引导对接融资需求,主动推进项目签约。 4、及时撰写合格的项目立项报告,按流程要求实施项目签约;协助对接业主,完成签约后续各种协调事宜。 5、定期复盘,积极学习酒店运营以及相关业务知识,不断提高开拓能力。

1.协助排查电商业务场景中出现的ERP系统问题,与服务商进行沟通跟进,助力业务顺利流转; 2.参与员工内购系统&内部领用系统的部门需求整理&流程对齐&功能模块设计,并协助完成系统的配置&功能测试工作; 3.协助跟进系统项目的推进进度,参与系统上线后的日常运维工作; 4.完成横向部门&主管分配下发的其他工作内容。
特斯拉为信息技术部开放 IT MFG DevOps AI 全职岗位(工作地点:特斯拉上海超级工厂)。若你是融合 AI 开发、DevOps 实践与制造业技术的全能专家,能在智能制造场景下高效应对挑战、解决复杂技术问题,拒绝重复低效的工作模式,那么该岗位正适合你。 IT MFG DevOps AI 是连接公司 IT 系统与生产制造环节的核心角色,身处智能制造落地的一线。你将每日对接 AI 技术研发、容器化部署与生产运维等多领域工作,通过技术实践支持公司优化生产流程、提升制造效率,助力实现智能制造转型的核心目标。 岗位职责 • 负责 AI 算法研发、模型优化与训练,聚焦生产线数据分析、质量控制、故障检测、自动化生产等场景,确保 AI 技术适配制造业务需求。 • 基于 Kubernetes(K8s)与 Docker 容器技术,完成 AI 解决方案的部署、监控与扩展,保障生产环境中系统的高可用性与稳定性。 • 参与 DevOps 流程建设,优化 AI 模型与系统的开发、测试、部署全链路,实现自动化部署、持续集成(CI)与持续交付(CD)。 • 与生产、质量控制、研发等制造相关部门对接,深入理解业务痛点,提供数据驱动的 AI 技术解决方案。 • 快速响应生产线上的技术需求与故障,排查 AI 系统、容器集群、网络环境等问题,减少对生产进度的影响,提升生产效率与质量。 • 跟踪 AI 与 DevOps 领域前沿技术(如工业大模型、云原生运维)及行业动态,推动新技术在制造场景的预研与应用,持续优化系统性能。
The Role TESLA is offering a full-time IT Support DevOps AI position in the Information Technology Department (Work Location: Tesla Giga Factory Shanghai). If you are a versatile expert integrating AI development, DevOps practices—someone who can efficiently tackle challenges, solve complex technical problems in user support and experience scenarios, and reject repetitive and inefficient work patterns—this role is perfect for you. IT Support DevOps AI is a core role connecting the company’s IT systems and user-facing processes, standing at the forefront of enhanced user support implementation. You will engage in work across multiple domains, including AI technology R&D, containerized deployment, and operational support. Through technical practice, you will support the company in optimizing user interactions, improving support efficiency, and contributing to the core goal of user experience transformation. Responsibilities • Undertake AI algorithm R&D, model optimization, and training, with a strong emphasis on fine-tuning (FT), supervised fine-tuning (SFT), reinforcement learning (RL), and advanced tuning techniques; focus on user support scenarios such as data analysis, query resolution, issue detection, and automated assistance to ensure AI technology aligns with user experience needs. • Complete the deployment, monitoring, and scaling of AI solutions based on container technologies like Kubernetes (K8s) and Docker, ensuring high availability and stability of the system in the operational environment, while integrating AI underlying technologies like neural networks and Transformer architectures for efficient performance. • Participate in DevOps process development, optimize the full lifecycle of AI model and system development, testing, and deployment, and realize automated deployment, continuous integration (CI), and continuous delivery (CD), incorporating RL-based optimization and model tuning for adaptive user support systems. • Collaborate with user support-related departments such as helpdesk, customer service, and product teams to deeply understand user pain points and provide data-driven AI technical solutions, leveraging SFT and attention mechanisms to enhance personalized user experiences. • Respond quickly to technical requirements and faults in user-facing systems, troubleshoot issues in AI systems, container clusters, and network environments, minimize impacts on user interactions, and improve support efficiency and satisfaction through advanced AI tuning and underlying model diagnostics. • Track cutting-edge technologies in the AI and DevOps fields (e.g., large language models with FT/SFT/RL integration, cloud-native operations) and industry trends, promote the pre-research and application of new technologies in user support scenarios, and continuously optimize system performance using techniques like model compression and quantization.