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Open nowPosted 516 days ago

世界模型算法工程师（北京/深圳）

x2-robot/index203 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now世界模型算法工程师（北京/深圳）x2-robot/index · Shenzhen, Guangdong, Chinese Mainland

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on x2-robot/index's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

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. x2-robot/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 516 days ago

x2-robot/index median: 1 days open

The posting

职位描述 1. 世界模型研发与优化：负责研发和优化世界模型算法，构建机器人的环境感知、状态预测和决策规划能力，提升机器人在复杂环境中的自主决策和适应性； 2. 多模态数据融合：开发适用于机器人端到端操作的多模态世界模型，整合视觉、语言、触觉等多模态信息，构建统一的环境表征和动态预测模型； 3. 时空特征学习：设计和优化机器人视频表征学习方法，从多模态数据中提取有效的时空特征表示，提升机器人的视觉空间推理和环境理解能力； 4. 强化学习与仿真：研究基于世界模型的机器人强化学习技术，开发高效的仿真环境，提升机器人在现实世界中的学习效率和泛化能力； 5. 技术前沿跟踪：跟踪世界模型、多模态学习、机器人学等领域的最新研究进展，推动技术创新和产业化应用落地。

职位要求 1. 专业背景：具有计算机视觉、人工智能、机器人学、认知科学等相关专业背景或相关行业工作经验； 2. 编程能力：熟练掌握主流深度学习框架（如PyTorch、JAX），具备优秀的编程能力和代码工程化经验； 3. 模型理解：对世界模型、生成模型（如Diffusion、GAN、Flow、Transformer等）有深入理解，有大规模模型训练经验，熟悉相关评测方法和基准测试； 4. 表征学习：熟悉多模态表征学习方法，能够从视频、图像、文本等数据中提取有效的特征表示，具备时序建模和动态预测经验； 5. 机器人技术：了解机器人端到端操作模型（如ACT、Diffusion Policy、OpenVLA、RT-2、pi0等）及视觉-语言-导航大模型的前沿进展； 6. 强化学习：具备机器人强化学习技术经验，有真实环境下的实施和优化经验，熟悉仿真到现实的迁移学习； 7. 分布式训练：具备大规模分布式训练经验，能够处理海量多模态数据和大型模型，熟悉模型并行和数据并行技术； 8. 学术背景：在ICML、NeurIPS、ICLR、ICCV、CVPR、CoRL等顶级会议发表论文，或在ACM等程序设计竞赛中获奖者优先考虑； 9. 个人素质：具有强烈的技术热情、创新思维和持续学习能力，能够独立思考和解决复杂技术问题。

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