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Open nowPosted 231 days ago

强化学习闭环训练工程师

momenta/talent222 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now强化学习闭环训练工程师momenta/talent · Beijing, 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 231 days ago

The posting

工作内容 1. 熟悉强化学习（RL）、离线强化学习（Offline RL）、在线闭环训练、Policy Optimization等方向的核心算法，精通PPO、DQN、SAC等主流强化学习算法的代码实现、训练逻辑及调优方法。 2. 对智能辅助驾驶场景下的交互数据、决策数据、仿真数据进行预处理、分析和特征工程，挖掘数据中的交互规律和决策痛点，支撑强化学习闭环训练的效果提升。 3. 结合公司已有的辅助驾驶真实路测数据、仿真场景数据，构建强化学习闭环训练体系，对辅助驾驶决策/规划Policy进行finetune，优化决策的安全性、舒适性和高效性。 4. 与辅助驾驶规划/控制工程师、仿真工程师合作，搭建高效的强化学习闭环训练平台，确保训练后的Policy能够无缝集成到实际辅助驾驶系统，保障工程可行性和落地效果。 5. 跟踪强化学习、闭环训练、决策智能等领域的最新科研进展和技术趋势，探索离线强化学习、多智能体交互训练等前沿技术在辅助驾驶场景中的落地应用，解决实际业务中的决策优化问题。

任职要求 1. 计算机科学、人工智能、自动化、机器人学或相关领域的985/211硕士以上学历。 2. 精通Python、C++或其它编程语言，具有扎实的数据结构和算法基础，熟练掌握强化学习相关代码编写和训练脚本开发。 3. 熟悉huggingface上的各种sota强化学习、决策模型项目，深入理解强化学习闭环训练的核心逻辑和工程实现细节。 4. 深入理解机器学习、深度学习、强化学习等人工智能核心技术，在强化学习闭环训练、辅助驾驶决策优化、Policy调优等相关领域有明确的项目经验。 5. 具备出色的分析问题和解决问题的能力，以及良好的团队合作精神。有责任心，能够适应快节奏的工作环境，并拥有良好的沟通能力。

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