文远知行仿真资深算法工程师

任职要求

1.Bachelor's or higher degree in Computer Science or an equivalent field
2.3+ years of relevant work experience
3.Proficiency in C++ and Python, including 1+ years of modern C++ in production environment
4.Experience with developing, optimizing and productizing deep learning model.
5.Solid understanding of common data structure and algorithm.
6.Experience with common deep learning software and hardware.

Plus:
1.Experience with GNN (Graph Neural Network), Transformer, BERT, LSTM, or other deep-learning models.
2.Experience with Reinforce Learning or other decision-making models.
3.Experience with ACM/NOI related competition.
4.Experience with solving open-ended questions and challenges.
5.Interest in learning from and optimizing for users.
6.Experience with recommendation algorithm, search algorithm, advertising algorithm, etc


职位描述:
1.总管文远知行仿真算法方向，带领和扩建团队。
2.制订技术和战略路线，领导技术攻坚，带领团队持续创新。
3.设计、实现和优化现有与下一代仿真算法与模型，包括智能障碍物（车辆、行人、非机动车辆等）行为模型、评估模型和基于场景的数据挖掘。
4.开发工具和自动化系统，处理大规模真实交通数据，并用于模型训练。
5.与文远其它部门密切合作，实现安全快速的软件算法迭代。这些部门包括：感知、决策规划、定位等等。

基本要求:
1.计算机或相关专业本科及以上学历
2.3年及以上相关工作经验
3.精通C++和Python，1年及以上在大型项目使用modern C++的经验
4.有丰富的开发、优化和产品化深度学习模型的经验
5.精通常见的数据结构与算法
6.熟悉常见的深度学习软硬件开发

加分项:
1.精通GNN、Transformer、BERT、LSTM等深度学习模型
2.精通强化学习或者其他决策模型
3.有ACM/NOI相关的经历
4.善于解决开发性问题和挑战
5.擅长基于用户的学习与优化
6.有推荐算法、搜索算法、广告算法等相关经验

工作职责

WeRide.ai is looking for an Engineering Tech Lead to join our Simulation team and help build the next generation of autonomous driving Simulation Engine, Algorithm and Modeling.

What you will do:
1.Oversee WeRide’s Simulation direction, lead and grow algorithm team in this scope
2.Define roadmaps, drive technical projects and provide leadership in an innovative and fast-paced environment.
3.Design, implement and optimize existing and next-generation of Simulation Algorithm and Modeling, including agent (vehicle/pedestrian/cyclist/…) behavior modeling, evaluation modeling and scenario-based data mining.
4.Build tools and automation pipelines to process large-scale real-world traffic data for model training.
5.Work across teams to facilitate safe and fast iteration of the autonomous driving software components: perception, motion planning, control, localization, and other.