X9546VV3 |【中文岗】Senior Operations Engineer

1 day ago


Kuala Lumpur, Kuala Lumpur, Malaysia TTUKoffer Full time 176,400 - 210,400 per year
  • 工作地点:吉隆坡 KL
  • 薪资范围:RM14,700 - RM17,700
  • 工作签证:不提供
职位亮点
  • 加入全球领先的AI基础设施服务提供商的国际团队,参与构建和运维尖端AI平台。
  • 独立负责全球用户的生产环境,直接影响核心服务的可靠性与性能。
  • 深度接触多云架构、GPU计算和自动化运维,积累高价值技术经验。
  • 跨文化协作环境,与中美技术团队紧密合作,提升中英文双语技术沟通能力。
核心职责
  • 端到端运维 ownership:全面负责AI基础设施产品(Model-API、Serverless、GPU实例)的可用性、延迟、性能与效率。
  • 故障响应与管理:作为生产事件第一响应人,深入排查根因(RCA),实施预防措施,并参与轮值待命。
  • 自动化与工具开发:设计和维护自动化脚本与工具,实现运维任务、部署和故障恢复的流程化。
  • 监控与告警体系:构建并优化监控告警系统(如Prometheus/Grafana),实现问题主动发现。
  • 基础设施即代码(IaC):使用Terraform/Ansible等工具管理云基础设施,保障环境一致性与可重复性。
  • 性能与成本优化:持续分析系统性能与资源使用,识别瓶颈并优化云平台(AWS/GCP/Azure)成本。
  • 跨职能协作:与中方工程团队密切合作,理解新功能、提供运维反馈,并确保新服务达到生产就绪状态。
硬性要求
  • 5年以上DevOps/SRE/云运维经验,有科技或云服务公司背景优先。
  • 精通至少一家主流云平台(AWS/GCP/Azure);具备容器化与编排技术实战经验(必须掌握Docker/Kubernetes)。
  • 熟练使用至少一种脚本语言(如Python/Go/Shell);掌握Terraform/Ansible等IaC工具。
  • 具备监控与可观测性工具(如Prometheus/Grafana/ELK)的实战经验。
  • 系统化的问题排查能力,能在压力下冷静处理复杂分布式系统问题。
  • 中英文双语流利(书面和口语),能胜任跨团队技术沟通。
  • 具备高度责任心和自驱力,适应远程/分布式团队独立工作模式。
  • 加分项:有GPU加速计算环境经验;熟悉MLOps工具(如Kubeflow/MLflow);了解Serverless技术及CI/CD流水线。
如何申请?

点击'Apply'申请或发送简历至[],邮件标题注明[申请 WBX9546VV3]。推荐奖金:成功推荐人选可获得推荐奖励。详情

[Mandarin-speaking Role] Senior Operations Engineer (SRE/AI Platform)
  • ​​Location:​​ Kuala Lumpur
  • Compensation:​​ RM10,000 - RM15,000
  • Visa Sponsorship:​​ Not Available
​​Job Highlights​​
  • Join the international team of a leading global AI infrastructure service provider to build and operate cutting-edge AI platforms.
  • Take end-to-end ownership of production environments for global users, directly impacting core service reliability and performance.
  • Gain deep exposure to multi-cloud architecture, GPU computing, and automated operations in a high-impact role.
  • Collaborate in a multicultural environment with engineering teams across China and North America, enhancing bilingual technical communication skills.
​​Key Responsibilities​​
  • End-to-End Service Ownership: Assume primary responsibility for the availability, latency, performance, and efficiency of AI infrastructure products (Model-API, Serverless, GPU Instances).
  • Incident Management & Response: Act as the first responder for production incidents, perform root cause analysis (RCA), and implement preventive measures. Participate in an on-call rotation.
  • Automation & Tooling: Design, build, and maintain automation scripts and tools to streamline operational tasks, deployments, and failure recovery.
  • Monitoring & Alerting: Develop and refine monitoring and alerting systems (e.g., Prometheus/Grafana) to enable proactive issue detection.
  • Infrastructure as Code (IaC): Manage and provision cloud infrastructure using IaC tools (e.g., Terraform, Ansible) to ensure consistency and repeatability.
  • Performance & Cost Optimization: Continuously analyze system performance and resource utilization to identify bottlenecks and optimize cloud platform (AWS/GCP/Azure) costs.
  • Cross-Functional Collaboration: Work closely with engineering teams in China to understand new features, provide operational feedback, and ensure production readiness of new services.
​​Must-Have Requirements​​
  • 5+ years of hands-on experience in DevOps, SRE, or cloud operations, preferably in a tech or cloud service company.
  • Expertise in at least one major cloud provider (AWS/GCP/Azure); practical experience with containerization and orchestration technologies (Docker/Kubernetes required).
  • Proficiency in at least one scripting language (e.g., Python, Go, Shell); solid understanding of IaC tools like Terraform/Ansible.
  • Hands-on experience with monitoring and observability tools (e.g., Prometheus, Grafana, ELK Stack).
  • Systematic problem-solving skills with the ability to troubleshoot complex distributed systems under pressure.
  • Professional fluency in both English and Mandarin (written and spoken) for effective cross-regional collaboration.
  • Strong sense of ownership and self-drive, with the ability to work independently in a remote/distributed team setting.
  • Nice to Have: Experience with GPU-accelerated computing; knowledge of MLOps tools (e.g., Kubeflow, MLflow); familiarity with serverless technologies and CI/CD pipelines.
​​How to Apply?​​

Click 'Apply' or send your resume to [] with the subject line [Apply to WBX9546VV3]. Refer a friend for this role and earn referral bonuses See details:


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