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Open nowPosted 213 days ago

研究科学家/工程师 - 世界模型（视频生成与预测）

wcn7iq2vq1am/86371186 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now研究科学家/工程师 - 世界模型（视频生成与预测）wcn7iq2vq1am/863711 · Shanghai, 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. wcn7iq2vq1am/863711 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. 58.1%60 days
This job: posted 213 days ago

wcn7iq2vq1am/863711 median: 1 days open

The posting

关于该职位 在这个岗位上，你将大规模训练和微调用于机器人应用的最先进的视频和世界模型，例如，从模拟到现实的视觉迁移、合成数据生成、基于视频的规划，以及用于策略评估的学习模拟。你的工作将直接塑造我们的机器人如何理解、预测和与物理世界互动。 主要职责 - 在机器人数据上对大规模视频和世界模型进行训练、微调并迭代，推动从架构设计和预训练到特定任务适配的实验，并通过复现和基准测试最先进的方法来建立强大的基线。 - 开发用于机器人的视频模型应用，例如视觉历史建模、基于视频的规划，使用世界模型作为学习模拟器进行策略评估和奖励估计，并使用世界模型设计数据增强框架（例如新颖视角合成、模拟到现实的风格迁移、轨迹条件视频生成），以扩展和多样化现实世界的机器人训练数据集。 - 构建并维护数据管道，用于整理、处理和扩充来自模拟和现实世界机器人交互的大规模视频数据集。 - 交付可部署的模型工件和评估协议，并与具身AI、大语言模型/视觉语言模型（LLM/VLM）和3D视觉领域的研究人员合作，将世界模型集成到机器人系统栈中。

资格要求 - 计算机科学、电气工程或相关领域的博士学位（优先）或硕士学位。 - 在大规模视频模型的训练、微调或数据处理（例如，视频扩散模型、自回归视频模型、视频变换器）方面有实际操作经验。 - 精通PyTorch/JAX，有分布式训练经验（FSDP、DeepSpeed、Megatron）。 - 对生成式建模、时间序列建模和大规模优化有扎实的理解。 资格要求 - 优先考虑 - 有将视频模型应用于机器人任务（从仿真到现实的迁移、合成数据生成、用于规划的视频预测或学习仿真）的经验。 - 具备机器人学习数据增强策略的经验，包括轨迹增强、视图合成或领域随机化 - 熟悉现实世界机器人数据管道和远程操作数据格式。 - 在顶级CS/CV会议（如NeurIPS、ICML、ICLR、CVPR、ICCV、ECCV）上的第一作者发表记录。 - 熟悉3D感知视频生成、多视图合成或神经场景表示。 - 跨领域经验将视频生成与具身AI、强化学习或机器人操作联系起来。 - 有领导或参与被广泛采用的开源模型，或已被集成到知名产品或平台中的研究的经验。

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