特斯拉2026/27届-项目管理实习生，工厂固件团队 Program Manager Intern, Factory Firmware Team
任职要求
BS/MS in Electrical Engineering, Mechanical Engineering, or equivalent Proven experience in managing end-to-end projects or product deployments from concept to successful launch Excellent interpersonal, communication, and collaboration skills, with the ability to thrive in a highly cross-functional environment Ability to work independently, with limited resources…
工作职责
工作地点：特斯拉上海超级工厂研发中心 要求时间：2025年年底或2026年1月开始实习，至少4个月，6个月以上优先，一周五天全勤 英文：流利，需与美国团队日常会议沟通 *针对2026届为常规实习，无转正机会。 The Role As a Program Manager intern, you will be responsible for a wide variety of cross-functional programs across system integration, vehicle software development, system validation, and issue triage support. In this role, you will manage the development and the introduction of several cutting-edge firmware integration projects, leveraging your expertise in system integration and driving results with Tesla's signature agility and speed. Responsibilities Manage cross-functional programs from end-to-end, covering a range of areas including firmware impacts driven by program change scope, firmware branch strategy, firmware trials, manufacturing setups and tests, firmware flashing, and coordination with hardware & firmware development teams and program teams. Develop and manage project plans and ensure on-time delivery. Work closely with engineering and manufacturing teams to effectively coordinate firmware development, trials, validation, & integration to the factory. Define and drive the schedule for upcoming new project launches and sustaining programs. Continuously evolve our processes to increase precision, dependability, and agility.
1.理解招聘系统核心价值与用户需求，运用产品运营思维支持策略制定与闭环优化。 2.具有跨部门协同能力，在直线经理的指导下参与制定，实施并持续优化跨区域、跨职能的端到端招聘工作流程，确保其标准化、数字化可扩展且高效。 3.协助开发工具包、培训材料及行为指南，赋能招聘团队与相关协作方。 5.协助数据看板功能迭代，推动数据逻辑与用户体验优化落地。 6.其他招聘运营日常事务性工作和项目支持。
1. AI Agent研究与实现：跟踪AI Agent、智能体等前沿技术，快速复现学术论文中的算法实现，构建原型系统并验证效果； 2. 大模型应用开发：基于现有大语言模型（LLM）开发智能应用，包括但不限于MCP（Model Context Protocol）集成、工具调用、多模态交互等功能实现； 3. AI驱动数据分析：探索和实现AI大模型在大数据分析场景中的应用，包括自动化数据处理、智能报表生成、数据洞察挖掘等； 4. 技术调研与落地：持续关注AI Agent框架（如LangChain、AutoGPT、MetaGPT等）的最新进展，评估并集成到实际项目中； 5. 知识沉淀与分享：整理技术文档，定期进行技术分享，协助团队提升AI技术能力；
工作地点：特斯拉上海超级工厂研发中心 要求时间：2025年11月或12月开始实习，至少4个月，6个月以上优先，一周五天全勤 英文：流利，需与美国团队日常会议沟通 *提供转正机会，应届生优先。 About the Role The Systems Validation team is responsible for system level testing of all vehicle product launches, new hardware introduction, new features or any software release. System Validation tests are primarily developed using python for complex and robust validation strategies and deliver automated solutions to execute those strategies efficiently and repeatedly, thus enabling rapid iteration and evolution of Tesla’s vehicle systems. This role will be responsible for firmware validation of the charging system, including developing validation strategies, test cases for new hardware and firmware, and building automation validation bucks for ACDC system, improve the automation. Required to complete system bench validation and vehicle level system validation for new HW and FW; This role will also require collaborating and support the firmware development and integration teams to root cause issue, to iterate and complete a mature and stable product; Come join a team of deeply knowledgeable and motivated engineers that strive to build the most robust, performant and reliable vehicles in the world, using cutting edge software and hardware development tools and practices. What to Expect l Deliver automation test setups to integrate charging ACDC subsystems with simulated and/or actual vehicle components; l Work with the cross-discipline development and design engineers throughout the engineering organization to ensure the charging subsystems are designed with appropriate requirements, interfaces and interactions to achieve specific vehicle functions. l Develop, document and execute comprehensive system and sub-system level test specifications and test plans based on system requirements. l Specify, design, develop and integrate test automation frameworks and tools l Report, track and debug issues with software and/or hardware releases l Investigate field issues through data analysis and issue reproduction.