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Open nowPosted 995 days ago

电商多模态大模型算法实习生-电商业务

ByteDance19,260 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now电商多模态大模型算法实习生-电商业务ByteDance · Shanghai, 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 995 days ago

ByteDance median: 27 days open

The posting

日常实习：面向全体在校生，为符合岗位要求的同学提供为期3个月及以上的项目实践机会。 团队介绍：Data-电商团队，负责电商创新项目的算法和大数据工作。依托于字节跳动产品，帮助用户发现并获得好物，享受美好生活。在这个团队，我们不仅要通过推荐和搜索算法帮助用户买到感兴趣的好东西，也要通过风控算法和智能平台治理算法去甄别违规行为，保护用户的购物体验；我们还要建设智能客服技术、大规模商品知识图谱来提升各个交易环节的效率；我们也要结合机器学习和运筹算法，来优化供应链和物流的效率和成本，并进一步提升用户体验；另外我们还会用人工智能来帮助商家提升经营能力。我们的使命：没有难卖的优价好物，让美好生活触手可得。

1、大模型算法研发：构建电商领域的大模型LLM底座，融合电商的知识，快速落地电商业务，例如：沉淀电商大模型预训练链路，研发电商NLP大模型，或者研发电商图文或者视频多模态大模型； 2、基础算法研发：持续建设和深耕NLP/CV/多模态基础预训练算法（BERT类算法），例如：沉淀&优化电商场景的预训练模型，包括超长文本/口语文本预训练，电商图片/视频自监督，适配电商商品的多模态表征学习等； 3、梳理&沉淀算法库，抽象算法接口，最大化提高算法/预训练模型的复用率，同时优化数据采集&模型训练&部署&推理的流程，提升研发效率； 4、技术输出：定期分享SOTA模型，赋能电商甚至公司级别的业务BU，沉淀专利和论文。

1、本科及以上学历在读，计算机等相关专业优先； 2、扎实的深度学习技术基础，有CV/NLP/多模态相关的项目经验，发表过高水平学术会议论文或者有竞赛经验者优先； 3、熟练掌握Python/C++等至少一门编程语言；熟练Pytorch训练框架；熟悉Hunggingface-Transformers框架； 4、熟悉常用的大语言模型架构优先； 5、了解模型压缩&推理加速的研究和技术进展，包括但不限于模型量化、剪枝、蒸馏、TensorRT推理优化等； 6、了解业界常用的大语言模型推理加速框架，如VLLM，TensorRT-LLM；了解混合精度训练、分布式训练等训练加速方法优先。

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