[Skip to main content](#main-content)

[OpenNash Jobs](https://jobs.opennash.com/)
[Hiring report](/reports/hiring/) · [All Tencent Holdings jobs](https://jobs.opennash.com/companies/tencent-holdings/) · [Search jobs](/search/)

Tencent Holdings · Hangzhou

# 腾讯游戏-大模型推理性能优化工程师/专家

Hangzhou 

Listed on Tencent Holdings’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2072330945872183296)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 腾讯游戏-大模型推理性能优化工程师/专家

## Job description

### Responsibilities
- 与大模型算法同学深度合作，联合优化，打造行业领先的高性能推理引擎，支持LLM/VLM/DiT等模型的高效部署；
- 推理性能极致优化、包括PD分离、低比特计算、并行优化、算子优化等，提升大规模分布式推理系统的整体效率；
- 支持主流GPU和异构AI芯片，优化大模型推理性能，打造极致性能成本优势。 Requirements
- 熟练掌握C/C++、Python编程语言，具备良好的coding和调试能力；
- 熟悉主流大模型推理框架，如vllm，sglang，tensorrt-llm等，具备语言、多模态模型大规模部署和优化经验；
- 熟悉并行策略，如数据并行、流水线并行等，熟悉NVLINK、GPU RDMA通信者优先；
- 熟悉各类深度学习网络和算子底层实现细节，有实操经验优先；
- 熟悉主流开源模型及其架构特点，具备针对不同模型进行分析优化的能力优先；
- 具备GPU、AI芯片体系结构知识，熟悉芯片特性，具备系统性能分析和调优经验优先。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Jul 19, 2026
- Last checked: Oct 19, 2026
- Listed for: 92 days
- Location: Hangzhou[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2072330945872183296)

## More jobs at Tencent Holdings

### [OG项目组-高级游戏客户端开发](https://jobs.opennash.com/companies/tencent-holdings/jobs/85357c54bf3ee2846d3f/)

Hangzhou

### [云基础设施可用性技术专家-AI 代码质量与可用性治理](https://jobs.opennash.com/companies/tencent-holdings/jobs/ba2ff97226326763d857/)

Hangzhou

### [开放世界-3C策划(上海)](https://jobs.opennash.com/companies/tencent-holdings/jobs/10cc867023684bcf7f55/)

Hangzhou

### [开放世界-关卡策划-新星引力计划(上海)](https://jobs.opennash.com/companies/tencent-holdings/jobs/6d877434876f54519c18/)

Hangzhou

OpenNash lists jobs from employers’ own careers sites and does not handle applications.
Dates come from the employer where stated; “first seen” and “last checked” are our own observations.

OpenNash Jobs · Official listings with dates and links to the employer. [Weekly hiring report](/reports/hiring/) · [Methodology](/methodology/)