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Open nowPosted 58 days ago

具身智能算法工程师/研究员（世界模型）

xiaopeng/index1,587 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now具身智能算法工程师/研究员（世界模型）xiaopeng/index · Shenzhen, Guangdong, Chinese Mainland

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The clock on this job

Early applications get read.

12.1% 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. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 58 days ago

xiaopeng/index median: 1 days open

The posting

【关于机器人中心】 小鹏机器人中心专注于构建面向未来的人形机器人系统，融合先进的人工智能、控制、机械与系统工程，打造能感知、理解、操作并与现实世界交互的下一代机器人。 【关于世界模型团队】 我们相信，让机器真正在物理世界里泛化的钥匙，不是记住一个个任务，而是让模型学会"世界如何运转"——这就是世界模型（World Model）。 我们要构建的，是一个能理解当下、预见未来、并据此行动的模型：它不再是面向单一任务的策略，而是一个吸收了海量物理动力学知识、能"想象"未来、能跨场景泛化的具身基础模型。我们的目标是超越现有操作模型的泛化边界，做出可泛化、可落地、可 scaling 的世界模型，并在真实机器人闭环上验证它的价值。 团队精悍、扁平，成员分布于深圳、上海与美国硅谷，聚集了一批世界一流的研究者与工程师。在这里，你将： 站在具身智能最前沿，啃"通用泛化"这个最硬、也最值得啃的问题； 打通 数据 → 预训练 → 仿真 → 部署 → 真机 的全栈链路，亲眼看着自己的模型在真实机器人上跑起来； 与来自顶级高校与工业界的同伴并肩，快速试错、快速迭代。 【我们在做什么】 围绕世界模型，我们打通从数据到真机的全栈：训练 World Action Model（WAM）统一"理解世界—预测演化—生成动作"、突破泛化边界；训练 World Simulation Model（WSM）做长时序、物理一致的生成式仿真，用于策略评估与合成数据；从互联网规模的视频中蒸馏世界知识；并以大规模分布式训练、推理优化与端侧部署的基建，让 scaling 真正跑得起来、落得下去；同时在世界模型的 loop 里探索强化学习，让策略在"想象"中自我提升。

1、计算机、人工智能、电子工程、自动化等相关专业，硕士及以上学历，对世界模型、具身智能、大模型交叉方向有强烈热情； 2、扎实的机器学习与深度学习基础，熟悉 Transformer / Diffusion / VLM 等主流模型； 3、在以下任一方向有研究、项目、实习或课程经验：多模态大模型、AIGC / 视频生成、强化学习、Robotics / 具身智能、3D Vision、大规模训练与推理系统； 4、熟练使用 PyTorch，掌握 Python（会 C++ 更佳），工程实现与调试能力强，能把想法快速跑成实验； 5、思维开放、谦逊、自驱，好奇心强、学得快，乐于啃硬问题并与团队高效协作。 【加分项】 1、以主要作者身份在 CVPR / ICCV / ECCV / CoRL / ICRA / NeurIPS / ICLR / ICML / SIGGRAPH 等顶会顶刊发表论文； 2、有多模态 / 大模型 / 世界模型 / 视频生成 / 机器人 相关的深度项目或开源贡献； 3、大规模分布式训练、CUDA / 算子优化、推理部署等系统方向经验（面向基建岗）； 4、ACM/ICPC、NOI/IOI、Kaggle、TopCoder 等竞赛获奖；扎实的数学功底； 5、熟悉世界模型 / 视频生成 / VLA 开源生态（如 Wan、Cosmos、OpenVLA 等），有实践或二次开发经验； 6、能用英文撰写文档、论文或进行技术交流。 7、有机器人真机开发测试经验者优先。 【我们提供】 1、世界级的研发平台与资源：充足算力、真实机器人系统与数据平台； 2、与国内外顶尖研究、工程团队共事，在一支精悍扁平的团队里做真正前沿的事； 3、充分的探索自由与快速成长空间，以及面向毕业生的系统培养机制； 4、让你的工作直接作用于真实世界的机器人，而不止于 benchmark。 如果你想亲手为机器造一个"世界"，让 AI 真正理解并作用于物理世界——欢迎加入我们。

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