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Open nowPosted 111 days ago

自动驾驶基础模型研究员

li/referral788 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now自动驾驶基础模型研究员li/referral · 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. li/referral postings stay open a median of 1 days.

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. 57.8%60 days
This job: posted 111 days ago

li/referral median: 1 days open

The posting

岗位介绍 面向下一代自动驾驶技术路线，打造以视觉为核心的基础模型能力。区别于传统“感知结果驱动规划”的范式，构建从图像中直接学习对驾驶动作有因果意义表征的模型体系，让 Planner 更直接地利用视觉特征完成决策，并通过端到端训练持续提升复杂场景、长尾场景和闭环驾驶表现。 团队当前重点方向包括：视觉 foundation model、泛特征建模、世界模型（World Model / World-Action Model）、几何监督、自监督学习、时序建模、场景理解，以及面向自动驾驶任务的大规模训练与迭代优化。 岗位职责 1. 负责自动驾驶基础模型的架构设计、训练与效果迭代，推动视觉泛特征在自动驾驶任务中的建模与落地； 2. 研究视觉表征学习、世界模型、未来状态预测、inverse dynamics、latent planning 等方向，并结合自动驾驶场景形成可验证的技术方案； 3. 探索 Planner 与 Vision Encoder 更深度耦合的端到端训练方式，提升模型对复杂交通参与者、长尾障碍物和开放场景的理解与决策能力； 4. 设计并验证多种辅助学习任务，包括但不限于几何监督、自监督任务、时序建模、场景理解、视觉辅助任务等，持续增强模型表征能力； 5. 负责关键实验设计、离线/闭环指标分析、问题归因和版本迭代，形成高效稳定的研发闭环； 6. 与感知、规划、数据、训练系统、工程部署等团队协同，推动研究方案向工程可落地和量产可演进方向发展。。

任职要求 1. 硕士及以上学历，计算机、人工智能、自动化、机器人、数学、电子工程等相关专业； 2. 具备扎实的深度学习基础，熟悉 Transformer、ViT、视频理解、时序建模、自监督学习等核心方法； 在以下一个或多个方向有较深入的研究或实战经验： 视觉基础模型 / 表征学习 世界模型 多视图几何 / 3D视觉 / 深度重建 视频理解 / 时序融合 / Future Prediction 多任务学习 / 模型蒸馏 / 量化 / 大规模训练优化 熟练使用 PyTorch 等深度学习框架，具备较强的模型实现、训练调优与问题分析能力； 具备良好的实验设计能力，能够独立完成方案验证、结果分析和方向判断； 对前沿技术保持高敏感度，能够快速理解并吸收相关论文成果，并转化为业务可落地方案； 具备较强的自驱力、沟通协作能力和工程意识。

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