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Open nowPosted 138 days ago

具身智能触觉算法工程师（触觉表征方向）

x2-robot/index203 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now具身智能触觉算法工程师（触觉表征方向）x2-robot/index · Shenzhen, Guangdong, 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. 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. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 138 days ago

x2-robot/index median: 1 days open

The posting

岗位背景 触觉感知是机器人理解接触、受力、材质和操作状态的重要能力。相比单一视觉输入，触觉能够为机器人在复杂交互过程中提供更细粒度、更实时的反馈信息，对提升操作稳定性、环境适应性和精细控制能力具有重要价值。 本岗位主要面向机器人触觉感知与多模态学习方向，关注触觉表征、触觉 encoder、触觉与视觉/语言/动作模型的融合，以及快慢脑式决策架构中的触觉信息建模。 岗位职责 1. 负责触觉信号表征学习、触觉 encoder 建模及相关算法研发。 2. 探索触觉信息与视觉、语言、动作、本体状态等多模态信息的融合方式。 3. 研究触觉在机器人操作策略、世界模型或动作模型中的建模与使用方法。 4. 参与快慢脑式决策架构设计，提升策略对实时触觉/力觉反馈的响应能力。 5. 参与触觉数据处理、模型训练、实验评估和算法迭代。 6. 与感知、控制、硬件和机器人平台相关同事协作，推动算法在真实系统中的验证。

1. 计算机、人工智能、机器人、自动化、电子信息、机械电子等相关专业本科及以上学历。 2. 熟悉深度学习、表征学习或多模态学习，具备扎实的模型训练与实验分析能力。 3. 熟悉 PyTorch 等主流深度学习框架，具备良好的工程实现能力。 4. 了解时序建模、Transformer、自监督学习、对比学习、生成式模型等相关方法中的一种或多种。 5. 对机器人感知、操作或具身智能方向有兴趣，理解多模态信息在机器人决策中的基本作用。 6. 具备较强的论文阅读、问题抽象和独立推进能力。 加分项 1. 有触觉传感器、力觉传感器、机器人操作或多模态机器人学习相关经验。 2. 熟悉 VLA、VLM、world model、policy learning、action model 等方向。 3. 有触觉表征、触觉语言对齐、机器人 foundation model 或具身智能相关项目经验。 4. 有真实机器人数据采集、模型部署或闭环实验经验。 5. 熟悉阻抗控制、柔顺控制、力控等机器人控制基础概念。

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