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Open nowPosted 145 days ago

具身基础模型研究员/工程师（后训练方向）

x2-robot/index203 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now具身基础模型研究员/工程师（后训练方向）x2-robot/index · Shenzhen, Guangdong, Chinese Mainland

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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 145 days ago

x2-robot/index median: 1 days open

The posting

我们在做什么 我们专注于具身大模型的后训练方法体系建设与前沿技术探索，致力于通过数据策略、模型架构适配、高效微调与推理优化等技术手段，持续提升基础模型在不同本体/任务的执行效果与泛化能力。我们的目标是构建一套标准化、跨本体可复用的后训练方法体系，为物流、制造、家庭服务等商业化场景提供高质量的模型落地能力。 我们拥有超大规模的真机操作数据、完善的多场景评测体系、多本体硬件资源与专业数采团队，以及从数据采集到模型训练再到真机验证的端到端闭环能力。

职位描述 1.研究和构建具身大模型的后训练方法体系，探索数据策略与混合训练方法，持续提升模型在多场景、多任务下的执行效果与泛化能力； 2.研究不同模型架构在后训练中的适配性与应用潜力，明确各架构对不同类型操作任务的适用边界； 3.探索高效微调与快速迁移技术，降低对海量新数据的依赖，缩短模型向新环境、新任务迁移的后训练周期； 4.研究操作记忆机制，提升模型对操作过程中历史观测、动作轨迹与环境状态变化的记忆能力，解决操作过程中的模型困惑与重复执行问题； 5.研究推理侧优化技术，包括丝滑推理、推理加速与实时反馈、推理时计算等方向，提升模型动作输出的流畅度与实时性； 6.负责后训练实验设计与大规模模型训练，持续迭代模型能力并通过真机实验验证效果，将研究成果推进到商业化项目落地； 7.跟踪具身智能、模仿学习、强化学习与多模态大模型等前沿方向，推动算法创新与方法体系演进。

职位要求 1.计算机科学、人工智能、机器人学等相关专业背景，硕士及以上学历； 2.对大语言模型/多模态大模型有深入理解，熟悉主流VLA模型架构的原理与训练流程； 3.熟练使用PyTorch，具备扎实的工程能力和独立解决问题的能力； 4.具备模型后训练相关经验，对训练/数据策略有深入理解； 5.具备强执行力，能快速深入新领域并把事情做出来； 6.有技术热情，关注前沿进展，具备良好的学术视野。

加分项 •有具身大模型（VLA / World Action Model）的后训练或微调经验，熟悉OpenVLA、π系列、WALL-OSS、Dream-Zero等模型，了解Diffusion Policy、Flow Matching等动作生成范式； •有机器人真机部署与调试经验，有完整的训练→真机验证闭环经历； •有大规模分布式训练管线的搭建或优化经验； •有多任务学习、迁移学习、元学习等方向的研究或项目经验； •熟悉模仿学习（IL）、强化学习（RL）、RLHF/DPO/CFG等后训练与对齐技术； •有推理优化相关经验（异步推理、RTC、Test Time Compute等）； •顶级会议（ICRA、CoRL、RSS、CVPR、NeurIPS等）论文发表或相关竞赛获奖。

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