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Open nowPosted 481 days ago

自动驾驶端到端算法工程师/TL

momenta/talent222 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now自动驾驶端到端算法工程师/TLmomenta/talent · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 481 days ago

The posting

方向1: 工作职责 (1) 负责 Deep Learning Planning 算法设计，实现与离线评测/实车路测 (2) 负责高速高架及城区等场景自动驾驶的量产交付，并逐步朝终局无人驾驶前进 (3) 负责 Deep Learning Planning 数据产线及离线评测的搭建与维护 任职资格 (1) 计算机、机器人、人工智能等相关专业，熟练使用 C++、Python，有良好的数据结构和算法基础及代码规范 (2) 有深度学习算法背景，和扎实的数学基础，且具备预测、规划的背景知识 (3) 有相关算法（Deep Learning Prediction，Deep Learning Planning，Deep Reinforcement Learning，Imitation Learning，Deep Generative Model等）经历的优先 (4) 有机器学习领域顶级会议期刊论文发表的优先

方向2: 岗位职责 1. 负责将最前沿的强化学习，监督学习的方法应用到自动驾驶规控领域； 2. 参与自动驾驶深度学习框架的搭建和维护，模型自动化生产流程架构设计与优化； 3. 参与深度学习算法在数据生产线的研发落地，保障路测数据的高效回流与使用； 4. 同感知/规控/测试团队紧密配合，负责量产嵌入式自动驾驶产品中的规控算法集成。 职位要求 1. 精通常用机器学习，强化学习、监督学习的方法，具有将这些算法应用到实际产品中的实战经验； 2. 熟悉 C/C++、Python， 有良好的数据结构和算法基础； 3. 较强的算法设计和实现能力，熟悉 Caffe/TensorFlow/Pytorch 等训练框架； 4. 有较强的研究能力优先，曾在领域内的顶级会议发表论文 (CVPR,ICCV)者优先考虑。 加分项 1. 复杂系统工程经验，优秀开源项目研发经历； 2. RoboMaster, RoboCup等机器人比赛或ACM竞赛获奖者； 3. 熟悉自动驾驶技术栈和主流Planning算法框架； 4. 有Robotaxi/Robotruck/无人配送/机器人等领域Planning算法落地应用经验。

方向3: 岗位职责 1. 负责无高精方案下NaviModel-道路结构认知(LaneGraph)相关算法设计验证工作； 2. 负责无高精方案 下NaviModel-实时导航相关算法设计验证工作； 3. 负责无高精方案下NaviModel算法迭代，高速/城区自动驾驶产品性能提升和交付。 职位要求 1. 计算机、机器学习、人工智能、机器人等相关专业，熟练使用C/C++、Python，有良好的数据结构和算法基础； 2. 有深度学习算法背景，和扎实的数学基础； 3. 具有DETR， 图神经网络，Deep Generative Model, Imitation Learning等研发经历者优先； 4. 有Online Mapping，道路拓扑生成，实时导航等相关经验者优先; 5. 有ACM等编程比赛获奖经历的优先； 6. 复杂系统工程经验，优秀开源项目研发经历。

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