Senior MLOps Integration Engineer - Deploy & Monitor AI

United Overseas Bank Limited (UOB); Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

United Overseas Bank Ltd in Singapore seeks a Senior Officer MLOps Integration Engineer to bridge data science and IT operations, focusing on deployment and monitoring of ML models within enterprise systems.

Responsibilities include designing ML pipelines, managing containerized workloads on AWS/Azure/GCP, and coordinating with data scientists and IT teams to ensure reliable model integration and governance.

Qualifications

• University degree in a quantitative field.
• Experience in MLOps and DevOps for ML systems.
• Strong Python programming skills.
• Experience with ML platforms and cloud services.

Responsibilities

• Design, develop, and maintain robust MLOps pipelines for model training, deployment, monitoring, and retraining.
• Implement and manage infrastructure for scalable ML workloads, including containerization and cloud platforms.
• Collaborate with data scientists, software engineers, and IT operations teams to ensure reliable model integration into apps.
• Develop and implement CI/CD strategies for ML models.
• Establish and maintain monitoring and alerting for model performance and data drift.
• Troubleshoot and resolve issues related to ML deployments and infrastructure.
• Ensure compliance with bank security and governance policies throughout ML lifecycle.
• Research and implement new MLOps tools and best practices for efficiency.
• Document MLOps processes and architectures for maintainability.

Skills

Python programming

MLOps pipelines

Docker

Kubernetes

CI/CD practices

Data engineering concepts

Strong communication

Team collaboration

ML concepts

Education

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field

Tools

MLflow

Kubeflow

SageMaker

Azure ML

Vertex AI

Docker

Kubernetes

AWS

Azure

GCP

Job description

United Overseas Bank Ltd in Singapore seeks a Senior Officer MLOps Integration Engineer to bridge data science and IT operations, focusing on deployment and monitoring of ML models within enterprise systems.

Responsibilities include designing ML pipelines, managing containerized workloads on AWS/Azure/GCP, and coordinating with data scientists and IT teams to ensure reliable model integration and governance.