Senior MLOps Engineer — Scale ML Deployments & Governance

East West Banking Corporation; Makati; Hybrid; PHP 1,800,000 - 3,000,000; Full time

Job summary

East West Banking Corporation in Makati seeks a Senior Manager to lead ML Operations. You will design and maintain scalable MLOps pipelines for deployment, monitoring, and governance of models across the org.

Collaborate with data science, engineering, and infra teams to ensure reliable, reproducible ML workflows that drive business value. Hybrid work arrangement with opportunities for growth, mentorship from industry experts, and a structured path for career progression in a dynamic banking

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, IT or related field; Master's is an advantage.
• At least 5 years in software eng, data platforms, or ML infra with 3+ years in MLOps.
• Experience with MLOps tools, cloud platforms, containers, and CI/CD for ML deployments.
• Proficient in Git, model versioning, and end-to-end ML lifecycle management.
• Strong analytical and problem-solving skills with cross-functional collaboration.
• Excellent communication and accountability, with governance and compliance focus.

Responsibilities

• Design, build, and maintain scalable MLOps pipelines for CI/CD and monitoring.
• Collaborate with Data Scientists and Engineers to transition models to production.
• Implement automated monitoring, logging, and performance tracking for models.
• Enforce best practices for model versioning, reproducibility, and lifecycle management.
• Manage model governance, access controls, and regulatory compliance.
• Lead drift detection and automated retraining initiatives to ensure model accuracy.

Skills

MLOps

Cloud platforms

Containerization

CI/CD

Git

Model versioning

Analytics

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

GCP

Azure

Job description

East West Banking Corporation in Makati seeks a Senior Manager to lead ML Operations. You will design and maintain scalable MLOps pipelines for deployment, monitoring, and governance of models across the org.

Collaborate with data science, engineering, and infra teams to ensure reliable, reproducible ML workflows that drive business value. Hybrid work arrangement with opportunities for growth, mentorship from industry experts, and a structured path for career progression in a dynamic banking