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Open nowPosted 5 days ago

模型数据策略Leader - TikTok

ByteDance19,208 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now模型数据策略Leader - TikTokByteDance · Shanghai, Chinese Mainland

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

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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. ByteDance postings stay open a median of 2 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 5 days ago

ByteDance median: 2 days open

The posting

团队介绍：TikTok是一个覆盖150个国家和地区的国际短视频平台，我们希望通过TikTok发现真实、有趣的瞬间，让生活更美好。TikTok在全球各地设有办公室，全球总部位于洛杉矶和新加坡，办公地点还包括纽约、伦敦、都柏林、巴黎、柏林、迪拜、雅加达、首尔和东京等多个城市。

TikTok ADSO（AI Data Service and Operations）团队负责支撑AI 模型训练、评估与优化的核心数据服务与运营。通过构建高质量、标准化的数据生产体系，以及建立全球化的精益运营模式，为TikTok产品各类 AI 能力的迭代提供稳定、规模化、高性价比的数据支持，推动 AI 技术在复杂业务场景中的深度落地。

加入我们，在真实的全球化 AI 业务中快速成长。你将与顶尖的算法、产品、工程团队协作，在实战中理解 AI 如何真正落地。

1、围绕LLM/多模态模型训练与迭代需求，设计数据生产方案，包括任务拆解、标签体系、抽样策略、难例挖掘、分层质检和验收标准，支撑SFT、RM、评测集、红队集、专项诊断集等数据建设； 2、搭建数据质量评估框架，定义一致性、准确率、覆盖度、缺陷率、返修率、风险样本召回率等指标，并通过分层抽检、交叉标注、仲裁机制和误差归因提升数据可靠性； 3、与算法团队协同分析模型负面案例，定位问题属于数据分布、标注标准、任务定义、提示词、推理链路还是评估口径，并将分析结果转化为可执行的数据优化方案； 4、推动数据流程工程化，包括任务配置模板化、规则校验自动化、质检脚本化、数据看板化和版本管理，提升大规模数据项目的交付效率与可追溯性； 5、建立模型效果回流机制，将离线评测、线上实验、人工审核结果和用户反馈映射到数据侧，持续优化训练数据分布、标注规范和评测体系； 6、管理跨语言、跨区域或多供应商交付场景，制定统一的数据标准、SLA、升级机制和风险预案，保证复杂项目在质量、时效和成本之间达到可控平衡，同时参与关键技术议题，包括数据配比策略、长尾样本补齐、对抗样本设计、安全与合规数据治理、标注指令优化、弱监督/主动学习等方向的落地探索。

1、理解机器学习/大模型训练的基本流程，熟悉训练数据、验证数据、评测数据在模型迭代中的不同作用，能够与算法同学高效讨论数据问题； 2、具备较强的数据分析能力，能使用SQL、Python或其他分析工具完成样本分布分析、质量诊断、指标拆解和问题定位，有看板建设或实验分析经验优先； 3、熟悉数据标注与质量管理方法，理解双盲标注、Golden Set、IAA、一致性校准、抽样检验、误差分析等常见机制，并能结合业务阶段做取舍； 4、有复杂AI数据项目经验者优先，包括但不限于搜索/推荐/内容理解/安全风控/对话系统/生成式AI等场景，有多模态数据、英文数据或出海业务经验优先； 5、具备较强的抽象与结构化能力，能够把模糊问题转化为可执行的数据任务，把经验规则沉淀为SOP、规范和平台能力，具有团队管理能力。

加分项 1、有与算法、工程联合推进平台化数据系统的经验，例如任务平台、质检平台、评测平台、数据资产管理平台等； 2、有Prompt设计、模型评测、Agent任务拆解、偏好数据建设、A/B实验分析或线上效果归因经验； 3、能够在英文环境下独立推进跨团队沟通，推动全球化协作项目落地。

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