Hybrid ML Ops Engineer: Production ML & CI/CD

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

Benefits offered by this job

Career development opportunities

Competitive salary and benefits

Performance-based incentives

Mentorship by industry experts

Defined career progression paths

Job summary

EastWest Bank is seeking an experienced ML Operations Engineer to join our hybrid team in Taguig. You will deploy, automate, monitor, and continuously improve ML models and data pipelines using Databricks, MLflow, and CI/CD frameworks, ensuring reliable production ML systems.

Work closely with Lead ML Ops Engineer to operationalize data science solutions. You will collaborate with Data Scientists and Platform Engineers, maintain platform standards, and contribute to scalable ML operations, data

Qualifications

• Bachelor's degree in a technical field.
• 3-5 years of experience in Data Engineering, ML Engineering, or ML Operations, with hands-on deployment and automation in production.

Responsibilities

• Support deployment, configuration, monitoring, and day-to-day ops of ML platforms built on Databricks and MLflow.
• Package, register, version, and deploy ML models to production with smooth release processes.
• Build and maintain CI/CD pipelines using GitLab and automated testing/validation.
• Monitor model performance, data quality, and drift to maintain production reliability.
• Collaborate with Data Scientists and Platform Engineers to operationalize ML solutions.
• Maintain deployment docs and platform standards for scalable ML operations.

Skills

Experience in Data Engineering / MLOps

Python programming

CI/CD mindset

Education

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

Tools

Databricks

MLflow

GitLab

Python

scikit-learn

XGBoost

PyTorch

Docker

Kubernetes

Airflow

Job description

EastWest Bank is seeking an experienced ML Operations Engineer to join our hybrid team in Taguig. You will deploy, automate, monitor, and continuously improve ML models and data pipelines using Databricks, MLflow, and CI/CD frameworks, ensuring reliable production ML systems.

Work closely with Lead ML Ops Engineer to operationalize data science solutions. You will collaborate with Data Scientists and Platform Engineers, maintain platform standards, and contribute to scalable ML operations, data