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Open nowPosted 951 days ago

用户创作大模型算法工程师-智能创作（北京/上海）

ByteDance19,206 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now用户创作大模型算法工程师-智能创作（北京/上海）ByteDance · Shanghai, Chinese Mainland

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  2. CV RocketCV written for this posting.

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

  4. CV RocketApplied on ByteDance's own form.

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The clock on this job

Early applications get read.

12.3% 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. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 951 days ago

ByteDance median: 2 days open

The posting

1、负责个性化计算与推荐/搜索系统的算法设计与优化，将用户行为、偏好、上下文等信号引入大模型与多模态模型中； 2、参与大模型后训练（Post-Training）体系建设，包括但不限于SFT/Reward Modeling/RLHF/RLAIF； 3、利用用户在线反馈（点击、停留、转化、偏好选择等）构建Reward信号，驱动LLM/多模态生成模型的持续优化； 4、设计并实现基于强化学习（RL）或对比学习的优化策略，用于提升生成质量、用户满意度和业务指标； 5、与产品、工程、运营等多团队合作，推动个性化大模型在真实业务场景中的落地和迭代。

1、扎实的编程能力，机器学习基础知识扎实，对解决具有挑战性问题充满激情； 2、关心产品体验，逻辑感强，善于思考，数据与客观事实驱动，具备良好的工程与算法协作能力，积极主动、有责任感，能与团队高效沟通和合作； 3、推荐/搜索/广告/机器学习相关背景，3年及以上算法相关工作经验，在个性化建模或推荐系统方向有扎实积累；在以下至少一个方向有深入研究或实战经验： 1）搜索/推荐系统 2）大语言模型（LLM）或多模态大模型 3）个性化生成（Personalized Generation）； 4、熟悉或参与过大模型后训练（Post-Training）流程，包括但不限于： 1）SFT（Supervised Fine-tuning） 2）Reward Model训练 3）RLHF/RL-based Optimization； 5、能够基于用户在线行为与反馈数据，构建有效的Reward/Preference信号，并将其用于LLM/生图模型的优化； 6、对强化学习（RL）、对比学习、排序学习等方法有理解，并能将其应用于生成模型或推荐/搜索场景。

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