JMP_AI Vehicle Motion Control Algorithm Expert（VM）

Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.

Responsibilities:

1.AI solution design (e.g., Apply reinforcement learning and learning-based control methods under vehicle dynamics and real-time constraints.)

2.Collaborate with system, calibration, and software teams to support integration, tuning, and vehicle testing.

3.Support the transition from prototype algorithms to scalable, SOP-ready solutions.

岗位职责:

1.人工智能解决方案设计(例如：在车辆动力学特性与实时性约束条件下，应用强化学习及基于学习的控制方法。)

2.与系统、标定及软件团队协作，为方案集成、参数调校及实车测试提供技术支持。

3. 助力算法原型向可扩展、满足量产交付（SOP）标准的解决方案转化落地。

Qualifications:

1.Master’s degree or higher in Artificial Intelligence, Robotics, Computer Science, Vehicle Engineering, Control Engineering or a related field.

2.2 years of experience in AI/Robotics/ADAS related industries.

3.Strong background in ML, RS, GenAI.

4.Hands-on experience with machine learning or reinforcement learning (e.g., PPO, SAC, DDPG).

5.Proficiency in Python and/or C++, with experience using PyTorch or Jax

任职要求：

1.人工智能、机器人学、计算机科学、车辆工程、控制工程或相关专业硕士及以上学历。

2.具备 2 年人工智能（AI）/ 机器人学 / 高级驾驶辅助系统（ADAS） 相关行业工作经验。

3.拥有扎实的机器学习、RS、生成式人工智能（GenAI）专业背景。

4.具备机器学习或强化学习领域的实操经验（例如近端策略优化 PPO、软演员评论家算法 SAC、深度确定性策略梯度算法 DDPG）。

5.熟练掌握 Python 和 / 或 C++ 编程语言，且具备 PyTorch 或 Jax 框架的使用经验。

With the rapid evolution of intelligent and electrified vehicles, to enable more adaptive, robust, and data-driven vehicle dynamics control, we are advancing the integration of AI-based control algorithms into production-oriented chassis systems.This position is part of a strategic initiative to develop learning-based vehicle control solutions for real-time on-vehicle deployment. The role focuses on applying machine learning and reinforcement learning techniques to the chassis control functions.The successful candidate will transform domain knowledge and physical models into scalable, production-ready AI algorithms, contributing directly to the next generation of intelligent chassis systems.

随着汽车智能化与电动化的快速发展，为实现更具适应性、稳定性且数据驱动的车辆动力学控制，我们正致力于将基于人工智能（AI）的控制算法，整合至面向量产的底盘系统中。该岗位隶属于一项战略项目，核心任务是研发基于学习的车辆控制解决方案，以实现车载系统的实时部署。岗位工作重心为将机器学习与强化学习技术，应用于底盘控制功能的开发。合格候选人需能够将领域专业知识与物理模型，转化为可扩展、可量产落地的人工智能算法，直接助力下一代智能底盘系统的研发进程。