视频数据标注 & 评测专家 / 负责人
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 49d ago
The date the source published, not the day we noticed it (2026-07-28). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
San Francisco, Bay Area
The description states no restriction of its own. This is the source's own tag.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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ashby employer's own board first seen 11d ago · last seen just now
The listing
岗位职责
视频标注
• 设计并落地各类视频标注任务与规范:caption(prompt 与视频内容对齐)、动作(action)、场景(scene)、风格、镜头 / 运镜、时序一致性、ranking / preference、badcase 分类等。
• 搭建标注质检体系:gold set、抽检、多轮 review、一致性(IAA)、reviewer 校准,保障大批量标注质量稳定可迭代。
• 管理标注供应商 / 众包团队,控制交付质量、一致性与返工。
• 根据模型 badcase 持续迭代标注规范(guideline)与标准。
视频评测
• 搭建视频生成评测体系:评测集 / benchmark 构建,评测维度与指标设计(画质、动作自然度、时序一致性、prompt 匹配度、坏帧 / 变形 / 闪烁等),人工 + 自动评测结合。
• 建立 badcase 分类与回流机制,把评测结果转化为可执行的数据补充和标注规范调整。
• 支持多版本模型对比,跟踪数据使用效果与模型改进。
协同
• 与算法团队对接,理解 PT / SFT / RLHF / Eval 各阶段对数据的不同要求,推动数据标准持续迭代。
任职要求
• 3 年以上相关经验,做过视频 / 图像 / 多模态数据的标注或评测(非纯文本 NLP)。
• 亲手做过相关工作,能清楚讲解不同视频标注任务之间的差异和具体做法。
• 熟悉标注质检体系,在 gold set、抽检、IAA、reviewer 校准等机制上至少有一套实操经验。
• 有与算法团队协作、推动 badcase 回流的经验。
• 较强的流程梳理与跨团队沟通能力。
加分项
• 直接做过视频生成 / T2V / VLM / 多模态模型的训练数据或评测。
• 理解 SFT / RLHF,清楚偏好数据与 ranking 在其中的作用。
• 管理过标注供应商 / 众包 / 专家团队,并能把控交付质量。
• 有从 0 到 1 搭建标注或评测流程的经验。