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Open nowPosted 213 days ago

实习-智能辅助驾驶生成式决策算法实习生

nio/campus867 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now实习-智能辅助驾驶生成式决策算法实习生nio/campus · Shanghai, Chinese Mainland

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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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 213 days ago

nio/campus median: 1 days open

The posting

参与面向智能辅助驾驶系统的基于 Classifier-Free Guidance（CFG）的生成式强化学习算法研发，提升智能辅助驾驶行为决策的可控性、多样性与安全性； 研究内容包括但不限于：语言/视觉/地图等多模态条件下的轨迹生成、CFG 在动作/轨迹空间中的引导机制设计等； 负责算法在仿真环境和实车数据上的开发、迭代、评估与部署，支持端到端智能辅助驾驶决策模块的落地。

在生成式模型（扩散模型、自回归模型）、强化学习、智能辅助驾驶行为预测/规划、多模态条件生成 等任一方向有项目或研究经验者优先； 计算机、人工智能、自动化、车辆工程等相关专业背景，有 CVPR/ICRA/IROS/CoRL/ICLR 等会议论文、技术报告或开源项目者优先； 精通 PyTorch，熟悉 Flow Matching、Diffusion 等框架，有 nuScenes / Waymo / Argoverse 2 等智能辅助驾驶数据集使用经验者加分； 理解 Classifier-Free Guidance 的原理与实现，并能将其应用于连续动作空间的生成任务； 具备良好的沟通、协作能力； 实习时间不少于 4个月，每周出勤 不少于4天，能尽快到岗者优先。

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