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Geely Automobile Holdings · 上海市, 中国

# 端侧大模型算法工程师

上海市, 中国 

Listed on Geely Automobile Holdings’s official careers site. Listed as of October 23, 2026. Check that it is still open and apply there.
[Apply on Geely Automobile Holdings’s careers site →](https://app.mokahr.com/social-recruitment/geely/102042#/job/d35589a5-33a1-4868-8416-3dc85c944976)

[OpenNash Jobs](https://jobs.opennash.com/) / [Geely Automobile Holdings](https://jobs.opennash.com/companies/geely-automobile-holdings/) / 端侧大模型算法工程师

## Job description

### 岗位职责
- 参与大模型在端侧设备的性能优化与模型部署落地。
- 深入研究生成式多模态大模型的量化、算子优化、内核融合、图优化等关键技术，显著降低模型尺寸与推理延迟。

### 深度挖掘并利用端侧AI硬件的算力潜力，包括但不限于
- 高通Hexagon DSP/NPU、MTK平台、CUDA平台
- 构建和维护端侧模型自动化优化与部署 pipeline，包括模型转换、量化、编译、测试和性能分析。

### 任职要求
- 熟悉C/C++或Python编程语言。
- 熟悉并掌握主流模型压缩技术，如量化（GPTQ/AWQ/SmoothQuant/SpinQuant）、剪枝、蒸馏及NAS。
- 熟悉MLLM/VLM/LLM推理框架（如vLLM、TensorRT-LLM、llama.cpp）及优化加速技术（如Speculative-Decoding、Flashattention）。
- 具备MLLM/VLM/LLM推理优化和加速技术的实践经验。
- 拥有深入研究精神、创新能力及持续学习意愿。满足以上2~5项任一要求即可。

### 加分项
- 熟悉GPU/NPU硬件架构。
- 有异构计算加速或芯片级性能调优经验。
- 有集成、定制和优化主流推理。 3、优化引擎（如TensorRT、ONNX Runtime、TVM、MLIR）及LLM专用框架（如vLLM、llama.cpp、TensorRT-LLM）经验，使其更好地适配目标硬件。
- 研究和落地前沿推理加速技术，如推测解码（Speculative Decoding）、PagedAttention、FlashAttention等，

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 23, 2026
- Last checked: Oct 23, 2026
- Listed for: Under a day
- Location: 上海市, 中国[Apply on Geely Automobile Holdings’s careers site →](https://app.mokahr.com/social-recruitment/geely/102042#/job/d35589a5-33a1-4868-8416-3dc85c944976)

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