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Open nowPosted 868 days ago

多模态数据工程师 - Seed Model

ByteDance19,268 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now多模态数据工程师 - Seed ModelByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.9% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 9 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 868 days ago

ByteDance median: 9 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、负责千亿级别海量多模态数据全生命周期管理，覆盖视频、图像等数据的存储架构设计、分布式处理、全链路安全管控、自动化数据校验与质量治理，深度结合OCR、ASR、视频语义切分技术，优化多模态数据清洗、结构化、标注流程，保障数据合规性与高可用性； 2、负责多模态数据链路基建的全栈研发，追求极致的处理性能与执行效率，基于Transformer、CNN架构特性优化数据处理链路的推理加速方案，打造高并发、低延迟、高可用的分布式多模态数据处理引擎，支撑百万QPS级别的数据处理能力，兼顾工程稳定性与算法执行效率； 3、负责大规模多模态数据的分析洞察与可视化体系建设，深度挖掘数据分布、数据质量、数据特征对模型预训练、SFT微调效果的关联影响，搭建可解释的数据洞察平台，为模型训练策略优化、效果迭代提供核心数据依据； 4、与算法、模型训练团队深度协同，端到端打造数据-训练-评测-优化的全链路闭环，深度适配LLM/VLM的SFT监督微调全流程需求，加速高质量训练数据的生产与筛选，支撑模型效果评测与数据迭代，落地企业级大模型数据相关部署方案； 5、负责多模态数据能力的产品化封装，搭建易用的数据分析、算法推理与可视化工具，降低团队内数据获取与使用门槛，最大化多模态数据在大模型迭代中的核心价值。

1、熟练掌握Python、Golang中至少一种主流编程语言，具备高并发、异步编程实战经验，有百万级QPS数据链路研发与调优经验者优先；经历、面试优秀者能适当放宽就业经验要求； 2、精通Hive、ClickHouse、MySQL、MongoDB、ElasticSearch等数据湖/数据仓库技术，深入理解底层实现原理，具备优秀的数据抽象、建模与分布式架构设计能力； 3、熟练掌握Hadoop、Spark、Flink、Ray等大数据处理框架，有千亿级大规模分布式数据处理系统的研发、运维与性能优化经验。

加分项： 1、具备扎实的深度学习理论基础，精通Transformer、CNN等主流模型架构，熟悉LLM、VLM的技术原理、训练范式与落地全流程； 2、熟练掌握LLM/VLM的SFT监督微调核心方法论，有相关技术的企业级落地与部署经验者优先； 3、熟悉大模型推理加速核心技术与实现方案，有相关产业界规模化落地经验、或顶会/顶刊相关学术成果者优先； 4、熟悉视频语义切分、OCR、ASR技术原理与落地应用，有多模态内容理解相关实战经验； 5、有通用大模型训练数据全链路建设、多模态数据治理相关完整项目经验。

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