Senior MLOps Engineer: Scale & Govern ML Pipelines

East West Banking Corporation; Taguig; On-site; PHP 2,009,000 - 3,125,000; Full time

Benefits offered by this job

Competitive salary

Career development opportunities

Mentorship

Job summary

East West Banking Corporation is seeking an experienced ML Operations Engineer to design, build, and maintain scalable MLOps pipelines in the Makati area. The role focuses on deployment, monitoring, and governance of machine learning models across the organization.

You will collaborate with data science, engineering, and infrastructure teams to enable reliable, reproducible ML workflows that support business goals and regulatory requirements.

Qualifications

• 5+ years in software engineering, data platforms, or ML infrastructure.
• At least 3 years in an MLOps-focused role.
• Strong expertise in MLOps tools and cloud platforms.
• Proficiency in Git, model versioning, and end-to-end ML lifecycle management.
• Excellent communication and collaboration with cross-functional teams.

Responsibilities

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

Skills

Analytical thinking

Problem solving

Cross-functional collaboration

Communication skills

Governance & compliance awareness

Education

Bachelor's degree in Computer Science or related field

Master's degree (advantage)

Tools

Git

Model versioning

Containerization (Docker/Kubernetes)

CI/CD for ML

AWS

GCP

Azure

Job description

East West Banking Corporation is seeking an experienced ML Operations Engineer to design, build, and maintain scalable MLOps pipelines in the Makati area. The role focuses on deployment, monitoring, and governance of machine learning models across the organization.

You will collaborate with data science, engineering, and infrastructure teams to enable reliable, reproducible ML workflows that support business goals and regulatory requirements.