智能驾驶闭环端到端研究员_CR

Company Description 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. Job Description • 基于camera、radar和lidar，研发用于自动驾驶的closed-loop E2E相关算法，例如用于驾驶的two-stage和one-stage模型。 • 参与车辆上ADAS E2E pipeline的设计与部署，包括上游和下游模块之间的交互。 • 负责于端到端相关的数据准备和corner case挖掘，支持模型训练于验证。 • 与博世中国及全球的业务部门合作，进行需求分析、技术转移，并评估新概念的市场吸引力。 • 在中国范围内侦察、识别和跟踪新技术趋势与新兴技术，分析其对博世研发战略的影响，并识别关键合作伙伴。 • Research and development of closed-loop E2E related algorithms for autonomous driving, based on camera, radar and lidar, such as two-stage and one-stage models for driving. • Participate in the design and deployment of ADAS E2E pipeline on vehicle, with interaction between upstream and downstream modules. • In charge of data preparation & corner case mining for E2E model training & validation. • Cooperation with Bosch business units in China and worldwide for requirement analysis, technology transfer, and to evaluate market attractiveness of new concepts. • Scouting, identification, and tracking of new trends and emerging technologies in China, deriving impacts on Bosch research strategy, and identifying key partners. Qualifications • 拥有计算机科学、电气工程、机电一体化、机械工程或相关专业的优秀硕士学位，博士学历更佳。 • 在E2E模型领域有扎实的知识，特别是在perception和AI planner方面。 • 熟悉E2E领域的SOTA方法，例如VAD、PDM-Hybrid、Diffusion Models、sparsedrive、diff-vla等。 • 对AI planner相关数据集（如NuPlan）有深入理解。 • 具备E2E ADAS研发经验者优先。 • 熟悉现代AI框架，如PyTorch、HR HAT。 • 具有在车载ADAS计算单元上设计和部署perception模块的经验。 • 熟悉Python或C++。 • 熟悉Linux操作系统。 • 具有ADAS传感器（如cameras、radars、LiDARs）相关经验。 • 具备国际经验者优先。 • 热爱创新，具备出色的问题解决能力和创业思维。 • 强大的团队合作精神，能够自主高效地工作。 • 优秀的沟通能力，英语口语和书面表达流利。 • Excellent master's degree, ideally PhD, in the field of computer science, electrical engineering, mechatronics, and mechanical engineering or related. • Strong knowledge in E2E model domain, especially one-perception and AI planner. • Strong knowledge in E2E SOTA methods, such as VAD, PDM-Hybrid, Diffusion Models, sparsedrive, diff-vla. • Deep understanding on AI planner datasets, such as NuPlan. • Experience on E2E ADAS research & development is a strong plus. • Familiarity with modern AI frameworks: Pytorch, OpenMMLab, HR HAT. • Experience with designing and deploying perception on onboard ADAS computation unit. • Familiarity with Python, or C++. • Familiarity with Linux. • Experience in ADAS sensors, such as cameras, radars, and LiDARs. • International experience is a plus. • Passion for innovation, problem-solving & entrepreneurial mindset. • Strong team player with an autonomous and efficient working style. • Excellent communication skills, fluent in English (oral and written).