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ClosedPosted 279 days ago

具身数据模型算法工程师

nwd4iy9rd2s/referral79 open roles

Where
Beijing, Chinese Mainland

This posting closed on 2026-10-23. 79 other nwd4iy9rd2s/referral postings are live.

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Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. nwd4iy9rd2s/referral 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 279 days ago

nwd4iy9rd2s/referral median: 1 days open

The posting

1.负责具身数据质量、预标注、高价值挖掘、多样性分析与数据 - 模型闭环算法研发，服务 VLA 模型训练。 2.质量建模与清洗：多模态数据（视觉 / 语言 / 触觉 / 状态 / Action）质量评估、异常识别、时空对齐与隐私脱敏；建立可解释的质量评分与错误类型体系。 3.预标注模型：基于 VLM / 视频理解 / 多模态大模型，研发动作切分、Caption、指令生成、对象识别等能力，落地数据生产链路。 4.高价值数据发现：从海量数据中挖掘高质量 / 高复杂度 / 长尾 / 边界样本；构建检索、聚类、去重与数据价值评估。 5.多样性与分布分析：搭建 "场景 × 任务 × 物体 × 动作 × 轨迹 × 终态" 多样性矩阵，量化覆盖度与分布差异，输出可视化看板。 6.数据 - 模型闭环：与 VLA 团队协作分析数据 / 质量 / 采样对模型效果的影响，反向定位数据缺口，推动采集、清洗与训练策略迭代。

1.本科及以上（CS / AI / 自动化 / 机器人 / 数学等相关专业） 2.熟练 Python + 至少一种深度学习框架（PyTorch / TF） 3.熟悉 VLM / 视频理解 / 多模态大模型 / VLA；理解表征学习、对比学习、检索、异常检测 4.能独立完成 "问题定义→算法研发→实验→部署" 闭环，跨团队高效协同 5.能熟练使用 AI Coding / Agent Coding 工具提效 【加分项】 机器人操作 / 自动驾驶 / 视频等多模态时序数据经验；大规模数据清洗 / 数据飞轮 / 数据配比优化经验；VLM / VLA / 世界模型 / 机器人学习项目经验；高水平论文 / 数据竞赛 / 开源贡献。 【岗位价值】 构建连接 "数据生产" 与 "模型能力" 的核心数据智能系统，直接影响 VLA 模型的训练效率、泛化能力与真实机器人表现。

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