- Kampung Ladang Melaka Malaysia
全职 MLOps Developer 工作, 薪水, Randstad Malaysia Melaka 公司招聘中 - Ricebowl
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职位描述
岗位职责
About The Company
Manufacturing industry producing electronics products
About The Job
We are seeking an MLOps specialist to architect the infrastructure that allows our AI models to live and breathe on the factory floor. You will be the bridge between model development and industrial production, ensuring our AI systems are scalable, monitored, and resilient enough for 24/7 manufacturing operations.
Frameworks: Proficiency with ML lifecycle tools like MLflow, Kubeflow, or DVC for model versioning and tracking.
Backend: Strong Python skills, particularly for creating robust API endpoints and managing microservices.
Security & Monitoring: Experience implementing SSO/MFA for AI services and
setting up real-time monitoring for model performance/drift.
Key Responsibilities
You will be reporting to General Manager
Manufacturing industry producing electronics products
About The Job
We are seeking an MLOps specialist to architect the infrastructure that allows our AI models to live and breathe on the factory floor. You will be the bridge between model development and industrial production, ensuring our AI systems are scalable, monitored, and resilient enough for 24/7 manufacturing operations.
Frameworks: Proficiency with ML lifecycle tools like MLflow, Kubeflow, or DVC for model versioning and tracking.
Backend: Strong Python skills, particularly for creating robust API endpoints and managing microservices.
Security & Monitoring: Experience implementing SSO/MFA for AI services and
setting up real-time monitoring for model performance/drift.
Key Responsibilities
- Model Deployment: Lead the transition of models from Jupyter notebooks into production-ready microservices.
- Infrastructure Automation: Build and manage the infrastructure required to support LLMs and RAG pipelines at scale.
- Observability: Implement logging and alerting systems to detect "model drift" or accuracy drops caused by changes in factory sensor data.
- Security Compliance: Ensure all AI tools and internal chatbots meet enterprise security standards and are integrated with company-wide authentication.
- Scalability: Optimize AI services to handle high-frequency data from multiple production lines simultaneously.
- Experience: 2-5+ years of professional experience in DevOps or MLOps, with a specific focus on deploying and maintaining machine learning models in production.
- Automation & CI/CD: Deep expertise in building automated CI/CD pipelines specifically for ML (using Git, Jenkins, or GitHub Actions) and containerization with Docker.
- Orchestration: Experience with Kubernetes for managing large-scale GPU workloads.
- Cloud/Hybrid: Experience managing hybrid environments (On-premise servers vs. Azure/AWS).
- Testing: Knowledge of automated testing for AI/ML (Unit tests for model logic).
You will be reporting to General Manager
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