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Tencent Holdings · Beijing

# 腾讯云 DataBuddy-机器学习平台高级工程师

Beijing Data & Analytics 

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=2100123321357221888)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 腾讯云 DataBuddy-机器学习平台高级工程师

## Job description

### MLOps全链路建设
- 负责数据、特征、训练、版本、评测、部署、推理、监控迭代全流程工程化建设，标准化AI研发交付流程；

### 企业级特征平台落地
- 主导 Feast 架构落地与优化，搭建离线/在线统一特征体系，完成特征物化、回填、版本管理与高并发在线查询，治理特征漂移与一致性问题；

### 自动化训练流水线
- 基于 MLflow/Kubeflow/Airflow 搭建训练调度、实验追踪、版本管理自动化流水线，提升算法迭代效率；

### 模型服务化工程
- 基于 Docker/K8s 完成模型容器化部署、灰度发布与弹性扩缩容，优化在线推理、批量预测性能，保障高可用、低延迟、高吞吐；

### AI可观测与稳定性
- 搭建数据、特征、模型指标、漂移、推理异常监控体系，形成告警与迭代闭环，保障线上模型长期稳定运行；
- 该岗位可 base 北京、深圳、杭州、上海。 Requirements
- 本科及以上学历，3年以上MLOps/机器学习平台工程落地经验，具备端到端AI工程体系搭建能力；
- 熟练使用 Python/Go 服务开发，具备高并发服务设计与优化经验；
- 精通 Docker、K8s，熟悉CI/CD、资源调度、灰度发布等生产落地；

### 核心技术栈
- ； 1）特征工程：精通Feast 架构与生产落地，熟练掌控离线/在线特征治理、Redis高并发查询、特征一致性优化； 2）MLOps工具链：熟练落地 MLflow、Kubeflow、Airflow，可独立搭建自动化训练与版本管理流水线； 3）模型部署优化：熟悉 PyTorch/TensorFlow 模型部署，掌握推理加速、量化、Batch优化等工程手段； 4）存储与计算：熟练使用 Redis、OSS/S3、MySQL，熟悉 Ray/Spark/Flink 大数据计算场景。

## 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=2100123321357221888)

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

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