Senior ML Ops Engineer — Hybrid, Growth & Impact

EastWest Bank; Makati; Hybrid; PHP 1,200,000 - 2,000,000; Full time

Benefits offered by this job

Career development and training

Competitive salary package

Performance-based incentives

Mentorship by industry experts

Defined career progression paths

Job summary

EastWest Bank is seeking a Senior ML Ops Engineer in Makati to lead end-to-end MLOps design, deployment, monitoring, and governance across the organization. The role collaborates with data science, engineering, and infrastructure teams to ensure scalable, reproducible ML workflows that align with business objectives.

The ideal candidate has 5+ years in software/data platforms or ML infrastructure, with at least 3 years focused on MLOps, and strong proficiency in cloud platforms, Git, CI/CD, and

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Information Technology, or related field (Master's preferred).
• At least 5 years in software engineering, data platforms, or ML infrastructure; minimum 3 in MLOps.
• Strong experience with MLOps tools, cloud platforms, containers, and CI/CD for ML deployment.

Responsibilities

• Design, build, and maintain scalable MLOps pipelines.
• Collaborate with Data Scientists and Engineers to transition models to production.
• Implement monitoring, logging, and performance tracking for model reliability.
• Enforce best practices for model versioning and end-to-end ML lifecycle management.
• Manage model governance and compliance with internal policies.

Skills

MLOps

Git

CI/CD

Cloud platforms

Communication

Analytical thinking

Education

Bachelor's degree in CS/IT/related field

Master's degree (advantage)

Tools

AWS/GCP/Azure

Containerization

Model versioning

Job description

EastWest Bank is seeking a Senior ML Ops Engineer in Makati to lead end-to-end MLOps design, deployment, monitoring, and governance across the organization. The role collaborates with data science, engineering, and infrastructure teams to ensure scalable, reproducible ML workflows that align with business objectives.

The ideal candidate has 5+ years in software/data platforms or ML infrastructure, with at least 3 years focused on MLOps, and strong proficiency in cloud platforms, Git, CI/CD, and