特斯拉项目管理实习生，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：2026年5月或6月开始实习，至少4个月，6个月以上优先，一周五天全勤 毕业时间：2026年或2027年 英文：流利，需与美国团队日常会议沟通 转正：表现优异且通过转正考核的情况下可以转正 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.
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.
我们是小红书中台大模型 Infra 团队，专注打造领先易用的「AI 大模型全链路基础设施」！团队深耕大模型「数-训-压-推-评」技术闭环，在大模型训练加速、模型压缩、推理优化、部署提效等方向积累了深厚的技术优势，基于 RedAccel 训练引擎、RedSlim 压缩工具、RedServing 推理部署引擎、DirectLLM 大模型 API 服务、QuickSilver 大模型生产部署平台等核心产品，持续赋能社区、商业、交易、安全、数平、研效等多个核心业务，实现 AI 技术高效落地！ 工作职责： 1、参与/负责研发面向大语言模型(LLM)/多模态大模型(MLLM)等类型模型的推理服务框架； 2、参与/负责KV Router、PD分离/EPD分离、KVCache管理、动态PD调整等分布式推理能力建设； 3、通过并行计算优化、分布式架构优化、异构调度等多种框架技术，打造高效、易用、领先的AI推理框架； 4、参与/负责构建推理框架的系统容错能力，包括但不限于请求迁移、优雅退出、故障检测、自愈等能力建设； 5、深度参与周边深度学习系统多个子方向的工作，包括但不限于模型管理、推理部署、日志/监控、工作流编排等； 6、与全公司各业务算法部门深度合作，为重点项目进行算法与系统的联合优化，支撑业务目标达成。
【职位介绍】 我们团队负责构建小红书推荐算法中台，提高内容分发效率，为海量用户提供极致的推荐体验。在这里，你将参与到推荐系统的全链路搭建和各类算法的研发，包括不限于大模型应用、多模态建模、深度学习、强化学习、迁移学习、表示学习、图学习等领域。我们希望对推荐、搜索、广告感兴趣的同学，加入我们一起研发世界一流的推荐引擎。 1. 负责推荐算法中台的全链路建设，抽象业务共性，敏捷高效支持各类推荐需求。 2. 负责业界先进推荐算法的研发和落地，包括但不限于大模型技术、多模态内容理解、召回算法、排序模型（粗精排）、长短期兴趣建模、多场景联合建模等。
中台稠密引擎组，是小红书负责建设通用深度学习训练推理引擎的团队，面向全公司LLM、多模态LLM、SD、传统CV&NLP等稠密计算型模型训练与推理的业务场景，打造高效、易用、业界领先的训练与推理引擎，为小红书社区、商业化、安全等众多业务方向提供先进的引擎能力，支撑业务持续提升训练推理效率、模型迭代效率与算法研发效率。 1、参与设计和实现深度学习后训练及微调的前沿算法（包括但不限于RFT、RLHF等），以适应多样化的业务场景； 2、结合业务数据和场景，评估选择最适合的微调算法，以支撑业务大语言模型（LLM）微调指标的提升； 3、与数据团队紧密合作，深入理解数据特性，参与设计实现数据提质算法引擎工具，产出高质量数据集提升模型微调效果； 4、与公司内各算法团队深度合作，参与或负责大语言模型、多模态大模型等业务场景的后训练端到端效果提升及落地； 5、密切关注业界 LLM 微调算法和数据提质领域的前沿论文，并整合新技术和算法到训练引擎中，提升框架的领先性；