Job Description SummarySystems engineering for reliability on system, image quality, hardware, software and service design to build quality product for customer, including setup the reliability tests methodology and identify the growth area for new product introduction programs with
Tätigkeitsbereich:Forschung & Entwicklung incl. Design Fachabteilung:Ex RD China Gesellschaft:Mercedes-Benz Group China Ltd. Standort:Mercedes-Benz Group China Ltd., Beijing Startdatum:sofort Veröffentlichungsdatum:18.08.2026 Stellennummer:MER000478Z Arbeitszeit:Vollzeit Bewerben Aufgaben Job Description To support RD China strategy of maximally utilizing local eco-system, as well
Find what drives you on a team with a more than 75-year history of discovery, determination, and innovation. As a global leader in high-tech filtration, separation, and purification, Pall Corporation thrives on helping our customers solve
Do you want to be part of a great international company in wind energy? If yes, Vestas has opportunities for you to further expand these capabilities in the wind industry. Vestas Technology & Operations Research &
The Clinical Operations Program Lead plays a pivotal role to provide input to optimize trial execution, coordinate governance interactions and product strategy. This role maintains accountable to the Global & China Project Team (GPT/CNPT) for oversight
Company: Qualcomm China Job Area:Engineering Group, Engineering Group Systems Engineering General Summary: General Summary Qualcomm Robotics is building next‑generation robotic platforms powered by Snapdragon technology. As a Robotics Simulation Engineer, you will develop and maintain high‑fidelity simulation
我们正在寻找一位 全栈工程师，参与核心 AI Agent 产品从架构设计、能力建设到生产落地的完整过程。你将参与 Web 产品、API 服务、Agent 编排系统、后台任务系统、数据层和部署流程等多个环节，和团队一起构建面向真实生产环境的 AI Agent 产品。 你将深度参与 AI Agent 系统的工程化建设，包括 Agent Loop、工具调用、任务编排、多步骤执行、上下文管理、模型路由、异步任务处理、结果持久化、错误恢复、日志追踪与系统可观测性等关键模块。这个岗位不是简单调用大模型 API，而是需要将 LLM 能力、业务流程、前后端系统和用户体验结合起来，构建可稳定运行、可持续扩展的生产级 Agent 产品。 在这个角色中，你需要理解 Agent 如何接收用户目标、拆解任务、选择工具、执行动作、处理中间状态、根据反馈继续推理，并最终产出可靠结果。你也需要关注 Agent 执行过程中的实际工程问题，例如任务超时、工具失败、重试策略、状态一致性、成本控制、并发执行、队列调度、数据追踪以及生成结果的可复现性。 你会和产品、设计、前端、后端和基础设施团队紧密协作，把 AI 能力落到真实的产品体验中。我们希望你既能理解前端产品形态和用户交互，也能深入后端服务、数据模型、任务队列和 Agent 编排系统，帮助团队搭建长期可维护、可扩展、可观测的 AI Agent 工程体系。