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Tencent Holdings · Beijing

# 微信-语音全双工对话大模型预训练算法工程师

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=2089544603412901888)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 微信-语音全双工对话大模型预训练算法工程师

## Job description

### Responsibilities
- 负责语音全双工对话大模型的架构设计与预训练，构建边听边说、实时打断、自然接话和连续对话能力；
- 负责音频理解模型预训练，提升语音内容、说话人、情感语气、副语言信息、环境声音及多人重叠语音的理解能力；
- 负责音频生成模型预训练，研究基于 Audio Token、Neural Codec、自回归、Diffusion 或 Flow Matching 的语音生成方案，提升音质、自然度、情感表现和生成稳定性；
- 负责全双工交互行为建模，包括回复时机、用户打断、抢话与让话、Backchannel、重叠语音和流式生成；
- 负责大规模音频预训练数据建设，包括数据清洗、去重、质量过滤、伪标注、Token 化及数据配比；
- 负责模型规模化训练、效果分析及训练稳定性优化，推动预训练模型的后训练、评测和产品落地。 Requirements
- 计算机、人工智能、语音信号处理等相关专业，硕士及以上学历；
- 具备全双工语音对话模型预训练经验，参与过端到端 Speech-to-Speech、Audio LLM、Omni Model 或类似模型研发；
- 具备音频理解模型或音频生成模型预训练经验，能够负责模型架构、数据建设、训练策略和效果分析；
- 熟悉全双工对话核心问题，包括 Turn-taking、End-of-turn Detection、User Interruption、Overlapping Speech、Backchannel 和 Streaming Generation；
- 熟悉 Audio Encoder、Conformer、Transformer、Audio Tokenizer、Neural Codec、自回归、Diffusion 或 Flow Matching 等技术；
- 熟练使用 PyTorch，具备大规模分布式训练经验，熟悉 DeepSpeed、Megatron-LM、FSDP 等训练框架；
- 具备较强的实验设计、问题定位和跨团队协作能力。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 12, 2026
- Last checked: Oct 19, 2026
- Listed for: 7 days
- Location: Beijing[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2089544603412901888)

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Dates come from the employer where stated; “first seen” and “last checked” are our own observations.

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