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Open nowPosted 158 days ago

VLA自动驾驶算法工程师

xiaopeng/index1,578 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen nowVLA自动驾驶算法工程师xiaopeng/index · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. xiaopeng/index postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 158 days ago

xiaopeng/index median: 1 days open

The posting

岗位简介：聚焦端到端自动驾驶 VLM/VLA 大模型研发，重点解决模型海外跨地域泛化难题，攻克海内外路况、交规、驾驶习惯、气候地貌差异导致的域偏移、鲁棒性差、长尾场景失效等核心问题，负责算法研发、迭代优化与海外量产落地。 主要职责 1、VLA大模型海外泛化研发：负责自动驾驶VLA/VLM端到端算法设计与迭代，针对海外多地域场景差异，优化模型环境认知、障碍物识别、行为预测与轨迹生成能力，解决跨域适配、认知偏差等核心问题。 2、强化学习跨域优化落地：基于PPO、DPO、GRPO、SAC等主流强化学习算法，搭建海外场景专属训练方案，完成跨域奖励设计、分布式训练、模型调优，提升模型海外复杂场景、恶劣天气、小众交通场景的泛化能力与稳定性。 3、全流程量产落地：主导算法从海外数据闭环、仿真适配、模型验证到实车测试、部署迭代的全流程工作，攻克海外样本稀疏、域迁移难、推理不稳定等工程问题，支撑业务规模化出海。

1、学历基础：计算机、人工智能、自动化、数学等相关专业硕士及以上学历，博士优先，具备扎实的深度学习与强化学习数理功底； 2、大模型能力：精通VLM/VLA端到端自动驾驶模型原理与全栈开发，熟悉大模型跨域泛化、域自适应、微调蒸馏技术，有智驾大模型落地经验优先； 3、强化学习能力：熟练掌握PPO、DPO、GRPO等算法，具备用强化学习解决问题的实战经验，有智驾/机器人项目量产落地经历； 4、自动驾驶认知：熟悉自动驾驶感知、预测、规划、控制全链路逻辑，兼具传统模块化与端到端模型研发认知； 5、工程与综合能力：熟练使用PyTorch，掌握分布式训练、模型优化、车载部署等工程能力；具备良好的逻辑攻坚、跨团队协作与项目推进能力，有技术带队经验优先。

加分项 1、有智驾VLA模型海外泛化、全球化适配、出海量产核心项目经验； 2、深耕跨域泛化、迁移学习、稀疏场景补齐方向，有相关落地成果； 3、参与过自动驾驶全球化技术路线、算法体系标准搭建； 4、拥有顶会论文、核心技术专利成果。

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