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Open nowPosted 71 days ago

校招-虚拟仿真平台研发工程师

nio/campus867 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now校招-虚拟仿真平台研发工程师nio/campus · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. nio/campus postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 71 days ago

nio/campus median: 1 days open

The posting

岗位核心目标： 负责主导设计与搭建高置信度的智能车控虚拟仿真平台。该平台将作为车辆控制算法（如VCU、智能底盘控制、智能车身控制）的“创新加速器”，核心任务是通过大规模、自动化的虚拟测试与训练，覆盖现实世界中难以触达的长尾场景，显著提升算法研发效率与产品质量，并确保算法模型从虚拟环境到车端部署的平滑迁移。

核心职责： 1. 平台架构与闭环搭建：主导设计并实现覆盖 “场景-仿真-模型-分析” 的全链路自动化闭环系统。重点构建平台的大规模并行计算能力与高效的场景吞吐能力，以支持海量测试与算法训练。 2. 高保真仿真环境构建：集成与验证高精度车辆动力学模型，确保虚拟车辆行为与实车的高度一致。 3. 借鉴先进仿真理念，负责集成车辆动力学模型，传感器模型与复杂环境模型，构建用于感知-认知-决策-执行闭环算法测试与验证的逼真虚拟世界。 4. 算法训练沙盒环境开发：为核心算法团队构建高效的仿真训练基础设施。该环境需能原生支持强化学习、模仿学习等前沿方法的训练流程，提供稳定的交互接口与奖励函数框架，并且能够程序化生成海量常规与边界场景，为数据驱动的控制算法提供丰富、多样的训练数据。 5. 测试验证体系与部署：建立模型在环、软件在环到硬件在环的完整验证链条。通过仿真平台提前暴露和收敛控制策略在边角案例中的风险，构建从虚拟模型到车端代码的可靠部署路径，大幅缩短开发周期。 6. 工具链产品化：将平台能力封装为标准化、易用的工具与服务，赋能整个研发团队，提升仿真技术在系统工程中的采纳度和价值。

1. 学历与经验：硕士及以上学历，计算机、车辆工程、自动化等相关专业，具备在车辆动力学，智能辅助驾驶或具身智能领域仿真平台的开发经验。 2. 核心技术能力（具备以下一个或多个方向的深入经验）： a. 精通Matlab/Simulink b. 精通 Python 和 C++，具备扎实的编程功底和系统设计能力。 c. 熟练使用 PyTorch 或 TensorFlow 等主流机器学习框架，并有在仿真环境中应用的相关经验。 3. 仿真领域经验（具备以下一个或多个方向的深入经验）： a. 车辆动力学仿真：精通 CarSim、CarMaker、VI-grade 等专业工具，并理解其与自定义算法平台的集成。 b. 仿真平台架构：有构建过大规模、自动化仿真系统的经验，熟悉任务调度、资源管理与数据流水线设计。 c. AI训练与仿真交互：具备将仿真环境与强化学习/模仿学习算法成功结合的项目经验，了解物理引擎（如 Isaac Sim）在控制领域的应用。 4. 系统思维：具备出色的业务理解能力和跨团队协作能力，能精准地将业务需求转化为高可用的技术方案。

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