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Open nowPosted 263 days ago

豆包大模型算法研究实习生-Data AML

ByteDance19,260 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now豆包大模型算法研究实习生-Data AMLByteDance · 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 263 days ago

ByteDance median: 27 days open

The posting

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。 团队介绍：Data AML是字节跳动的机器学习中台，为抖音/今日头条/西瓜视频等业务提供推荐/广告/CV/语音/NLP的训练和推理系统。为公司内业务部门提供强大的机器学习算力，并在这些业务的问题上研究一些具有通用性和创新性的算法。同时，也通过火山引擎将一些机器学习/推荐系统的核心能力提供给外部企业客户。

1、跟踪并探索LLM/Agent/多语言等前沿方向，面向真实生产力场景（如：信息分析与处理、客服与销售、搜索与推荐、办公自动化等）提升效果，沉淀通用可规模化的方法论与系统能力； 2、围绕LLM/Agent/多语言能力与训练范式开展探索与优化，包括但不限于：LLM能力优化：指令遵循、复杂推理、长上下文、生成质量与幻觉治理等；Agent能力提升：规划与决策、工具调用与推理、上下文管理与记忆、长程任务和多Agent等；多语言能力建设：多语言指令遵循与复杂推理、多语言检索与知识增强、小语种与跨语言一致性等；训练与优化方法：大规模数据与环境扩展、奖励/偏好建模（生成式奖励、RLAIF/RLHF等）、端到端强化学习等； 3、挖掘现实世界高价值任务，设计科学严谨的量化评测体系，推动模型智能持续提升，为广大企业和开发者提供顶级的大模型服务。

1、2027届本科及以上学历在读，计算机、软件工程等相关专业优先； 2、扎实的深度学习/NLP/RL基础，有靠谱想法且动手能力强，出色的独立分析和解决问题的能力，能够深入定位并系统性解决大模型优化中的关键问题； 3、在LLM/Agent/多语言有扎实积累，在NeurIPS/ICML/ICLR/ACL/EMNLP等顶会发表过相关高质量论文，主导过相关且有影响力的项目者优先； 4、优秀的代码能力（熟练Python/C++），在ACM/ICPC、NOI/IOI、Top Coder、Kaggle等比赛获奖者优先； 5、对AI的实际效用和突破性应用充满热情，敢于挑战未知问题，良好的自驱力和沟通协作能力，并愿意把前沿研究转化为可验证、可上线、可规模化的能力。

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