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Tencent Holdings · Beijing

# 混元大语言模型后训练算法工程师-Memory方向（北京/深圳/上海）

Beijing 

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=2046923451989651456)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 混元大语言模型后训练算法工程师-Memory方向（北京/深圳/上海）

## Job description

### 长期记忆机制研发
- 负责大模型长期记忆全链路算法设计，实现记忆抽取、存储、检索、更新、遗忘，解决跨会话记忆一致性、冲突与时效性问题；

### 个性化用户建模
- 基于用户交互、行为数据构建用户模型，挖掘用户偏好、表达习惯，驱动模型动态适配，提升个性化交互体验；

### 记忆方向模型后训练
- 使用 SFT/RLHF/ 奖励建模等技术，把记忆调用、准确性、个性化目标转化为训练信号；构建高质量训练数据，搭建用户反馈驱动的模型迭代闭环；

### 评测体系搭建
- 设计记忆、个性化相关评测指标，构建自动化评测集与线上实验体系，评估召回、幻觉、隐私风险等；

### 前沿技术落地
- 跟踪 Memory Agent、持续学习等前沿方向，推动技术成果业务落地。 Requirements
- 计算机、AI 等相关专业硕士及以上学历；
- 精通 Transformer 与大模型训练原理，在长期记忆、RAG、个性化 LLM、超长上下文、大模型 + 用户画像任一方向有扎实实践；
- 熟悉 SFT/RLHF/ 奖励建模，能将记忆、个性化目标转化为训练信号优先；
- 有向量库、知识图谱、记忆 Agent 框架、多轮对话状态管理等实战经验优先；
- 算法与工程基础扎实，熟练 Python，掌握 PyTorch/TensorFlow；
- 熟悉分布式训练、Megatron-LM/DeepSpeed/vLLM，有百亿 + 大模型调优经验优先。

## 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: Beijing[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2046923451989651456)

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