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Open nowPosted 9 days ago

具身数据效能专家 - Seed Model

ByteDance19,122 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now具身数据效能专家 - Seed ModelByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

12.4% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 5 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.4%7 days
  4. 20.0%14 days
  5. 35.5%30 days
  6. 58.6%60 days
This job: posted 9 days ago

ByteDance median: 5 days open

The posting

团队介绍：字节跳动 Seed 团队成立于 2023 年，致力于寻找通用智能的新方法，追求智能上限，为科技和社会发展作出贡献。

Seed 团队在 AI 领域拥有长期愿景与决心，团队研究方向涵盖 MLLM、GenMedia、AI for Science、机器人等，在中国、新加坡、美国等地设有实验室和岗位。目前，团队已推出业界领先的通用大模型以及前沿的多模态能力，支持豆包、即梦、TRAE 等超过 50 个应用场景，并通过火山引擎开放给企业客户。第三方数据显示，豆包 App 用户量在中国市场排名第一，豆包大模型日均 Token 调用量行业领先。

1、负责跨来源数据生产效能分析与优化，面向各类数据获取方式，建立统一的产能、质量、成本、交付周期和资源利用率分析框架，识别影响有效数据产出的关键瓶颈，推进优化，并量化改善效果； 2、参与跨来源数据获取策略与生产规划，根据模型训练、评测和研发需求，分析不同数据来源的质量、成本、产能、交付周期及适用场景，为数据获取策略、生产计划和资源配置提供分析依据，推动不同生产方式的组合优化，提升跨来源生产协同效率； 3、探索新的具身数据获取与生产模式，关注数据转换、视频数据筛选与结构化、自动化数据处理等方向，评估其规模化生产的可行性、数据质量、单位成本和模型应用价值，通过实际场景验证推动有潜力的生产模式从技术探索走向稳定交付； 4、识别生产规划、任务分发、进度跟踪、质量检查、异常分析和经营复盘中的自动化机会，运用Agent、Harness、AI Coding及相关工具，构建可执行、可追踪、可持续迭代的运营工作流，推动重复性工作自动化，减少人工协调与低效操作； 5、建设跨来源生产分析体系，提升对产能、成本、质量、交付进度及异常情况的可见性，将成熟的分析方法、工作流和业务实践沉淀为可复用工具，支持不同数据来源与生产场景的规模化扩展； 6、推动数据需求、质量与生产效能形成闭环，与数据产品、模型、评测及运营团队协作，理解模型能力缺口和研发需求，分析不同数据需求对生产成本、质量和交付周期的影响，结合数据交付及后续模型使用效果，推动生产策略和资源投入持续向高价值数据需求倾斜，同时推动生产流程标准化与持续改善，梳理生产流程中的共性问题，沉淀统一的指标口径、协作接口、分析方法和可复用工具，通过生产复盘、异常归因和改善效果追踪，持续提升数据生产效率，减少重复建设和跨团队协作成本。

1、本科及以上学历，机器人/自动化/计算机/AI相关专业优先； 2、具备优秀的系统思维、问题抽象与业务判断能力，能够从复杂的生产运营问题中识别关键约束，将模糊问题转化为可验证的假设、改进方案和实际业务结果； 3、积极使用Agent、Harness、AI Coding及自动化工具解决实际问题，能够独立探索和搭建工作流，将AI能力应用于真实业务流程，并持续验证其效果； 4、具备较强的生产效能分析与经营判断能力，能够围绕有效数据产出、单位有效数据成本、质量、交付周期和资源利用率进行分析，识别瓶颈、评估投入产出并推动持续改善； 5、具备较强的跨团队协作与项目推进能力，能够与业务、产品和技术团队共同解决复杂问题，推动分析结论转化为工具、流程和实际业务改进，而不局限于提出建议或输出报告； 6、具备良好的流程抽象与工具化能力，能够将依赖个人经验的工作方式沉淀为可复用的工作流、自动化工具和持续迭代机制；对AI、数据和机器人有浓厚兴趣，愿意深入理解不同数据来源、生产方式与模型训练需求之间的关系，并持续探索新技术对传统生产运营模式的改造。

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