智能驾驶闭环端到端研究员_CR
- Full-time
- Legal Entity: Bosch (China) Investment Ltd.
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).