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Open nowPosted 150 days ago

大模型Agent研发实习生（Agent Harness与平台方向） - TikTok算法

ByteDance19,260 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now大模型Agent研发实习生（Agent Harness与平台方向） - TikTok算法ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 27 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 150 days ago

ByteDance median: 27 days open

The posting

团队介绍：TikTok搜推算法团队，负责TikTok短视频产品的基础推荐、搜索算法，加入我们，你能接触到包括搜索、用户增长、社交、直播、内容创造、内容消费等业务场景，直接为核心用户体验负责，支持产品在全球赛道上高速发展。我们的工作内容包括大规模推荐算法的优化、复杂约束的优化问题的解决、多模态大模型的落地，并着力研究下一代AI Search和Chatbot的核心研发技术，包括不限于Multi-Agent、Agentic RL、Harness、Loop Engineering，探索强化学习在大模型时代的新范式。在这里，你可以深入钻研机器学习算法的改进和优化，探索前沿的技术；可以感受不同文化的碰撞，激发认知；可以通过对产品和内容生态的深度分析，影响产品未来的发展方向。

ByteIntern：面向2027届毕业生（2026年9月-2027年8月期间毕业），为符合岗位要求的同学提供转正机会。

1、Agent Harness研发：参与任务规划、工具调用、上下文与记忆管理、多Agent协作及异常恢复等核心能力建设，探索提升长程任务执行质量与可靠性的方法； 2、知识库与上下文工程：整合技术文档、代码和实验记录，开发知识处理、检索与更新流程，探索RAG和上下文组织方法，提升Agent对复杂研发任务的理解能力； 3、Benchmark与自动化评测：围绕真实研发场景构建任务集和评测工具，分析任务成功率、结果质量、时延与成本，通过运行轨迹和失败案例定位问题，设计实验并验证改进效果； 4、云端Agent平台开发：参与Agent开发、调试与运行功能建设，开发沙箱执行、任务调度、运行观测及结果展示等模块，提升平台的稳定性与开发者体验； 5、前沿探索与应用落地：跟进Agent领域的最新技术和开源项目，与推荐算法工程师合作，探索代码理解与开发、实验分析、问题排查等应用场景，完成有价值的复现、创新验证和工具落地。

1、2027届本科及以上学历在读，计算机、软件工程、人工智能等相关专业； 2、具备扎实的编程基础、数据结构与算法知识，熟悉Python，具有良好的编码和调试习惯；对大模型与Agent有持续兴趣，并有实际搭建经验；个人项目、课程项目、科研或开源实践均可，能够清晰说明设计思路、遇到的问题及改进过程； 3、了解大语言模型应用的基本原理，对工具调用、任务编排、RAG、上下文管理或Agent评测中的一项或多项有实践和理解； 4、有独立思考和动手能力，积极主动，能够提出想法并付诸实践验证；愿意探索开放性问题，能够拆解任务、开展实验并总结结论； 5、具备良好的学习能力、责任心和沟通协作能力，关注工具的实际使用效果，愿意结合评测结果与用户反馈持续优化。

加分项 1、有Agent Harness、Coding Agent、多Agent系统、知识库或自动化评测相关项目经验； 2、有后端服务、云端平台、开发者工具或高质量开源项目开发经验； 3、了解推荐、搜索或机器学习，有召回、排序、模型训练或实验分析经验，推荐系统经验不是必备条件； 4、欢迎在简历中附上项目、代码仓库或Demo，我们期待了解：你主动解决过什么问题、如何搭建Agent，以及如何验证它做得更好了。

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