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Open nowPosted 183 days ago

【实习】端侧AI的复杂任务处理与模型优化技术研究-豆包手机助手

ByteDance19,258 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now【实习】端侧AI的复杂任务处理与模型优化技术研究-豆包手机助手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 23 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%7 days
  4. 17.6%14 days
  5. 34.3%30 days
  6. 43.5%60 days
This job: posted 183 days ago

ByteDance median: 23 days open

The posting

团队介绍：我们隶属于产品研发与工程架构部，是字节跳动在智能硬件领域的软件技术攻坚力量—— 聚焦 AI 与智能硬件的深度融合，以 “让人与设备的交互更自然、更便捷” 为目标，探索前沿 AI 技术的落地场景，打造行业领先的智能硬件综合解决方案。 在这里，你将与一支顶尖技术团队并肩： -直击 AI 与硬件结合的核心技术难题，参与从 “技术探索” 到 “场景落地” 的全链路研发； -主导或深度参与关键技术突破，用创新定义智能硬件的交互未来； -站在行业前沿，将技术理想转化为千万用户可感知的产品体验。 如果你心怀对技术的热忱，渴望在 AI 与智能硬件的赛道上突破自我、创造价值，我们期待你的加入，与我们一起解锁更多技术可能，共筑智能交互的新生态！

课题介绍： 聚焦扩散模型（如 Stable Diffusion）精简训练、多意图推理编排及个性化记忆建模，解决多意图理解、任务动态规划、记忆模型稀疏性及模型轻量化部署等挑战，推动智能助手、图像生成等场景应用。

课题挑战： 1、精准理解用户输入中的多意图，推导意图间关系，设计任务推理方法； 2、应对行为数据稀疏性，基于长期行为设计有效特征提取与建模方法，构建个性化的记忆模型，提升用户交互的精准度与体验； 3、如何在保持生成质量的前提下，精简Stable Diffusion等扩散模型以适应端侧设备； 4、实现通用化GUI自动化操作，支持多种设备界面。

课题价值：探索大模型在端侧的能力并结合对用户的个性化数据的分析和建模，在保护用户隐私的情况下，提供更高性能、低延迟的更智能的用户使用体验。

1、2027届及以后毕业，博士在读，计算机、人工智能、计算机视觉、数据科学相关专业； 2、扎实的机器学习、NLP/CV/序列建模等基础，具备多模态数据处理等研究背景； 3、熟悉Transformer、Diffusion、GAN、CNN/RNN等模型基础结构； 4、在NeurIPS/ICML/ICLR/ACL/EMNLP/CVPR/ICCV/ECCV等顶级会议上发表论文者优先； 5、优秀的代码能力、数据结构和基础算法功底，熟练C/C++或Python； 6、出色的问题分析和解决能力，有自主探索解决方案的能力。

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