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Meituan · 北京市 +1 more

# 【大模型北斗实习】大模型模型压缩技术探索

北京市 +1 more 

Listed on Meituan ’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Meituan ’s careers site →](https://zhaopin.meituan.com/web/position/detail?highlightType=campus&jobUnionId=3153792897)

[OpenNash Jobs](https://jobs.opennash.com/) / [Meituan ](https://jobs.opennash.com/companies/meituan/) / 【大模型北斗实习】大模型模型压缩技术探索

## Job description

本课题专注于大模型前沿压缩技术探索，通过压缩技术降低大模型的推理部署成本。

### 课题研究内容包括但不限于
- 探索多种模态（文本、语音、视觉）的模型压缩技术，不限剪枝、蒸馏、稀疏、量化、低秩化。
- 探索新轻量化结构，不限 MoE、Mamba、Sparse-Attention、MTP，实现训练和推理的协同优化。
- 探索低精度量化算法，以及新型量化格式，不限预训练和后训练过程，实现大模型的极致压缩。
- 高性能算子设计和开发，实现极致的压缩推理性能。 1）熟悉常用的模型压缩技术：剪枝、量化、蒸馏、稀疏化。 2）熟悉 vLLM、SGLang 等开源推理框架。 3）熟悉 Megatron、DeepSpeed 等开源训练框架。

### 加分项

1）有影响力的开源项目中做出过核心贡献。 2）发表过高水平论文优先（如ICLR,ICML,ACL,EMNLP等）。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 19, 2026
- Last checked: Oct 19, 2026
- Listed for: Under a day
- Location: 北京市 +1 more[Apply on Meituan ’s careers site →](https://zhaopin.meituan.com/web/position/detail?highlightType=campus&jobUnionId=3153792897)

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