MLOps Engineer for Credit Risk Production & CI/CD

AEON Credit Service (M) Bhd; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

AEON Credit Service (M) Berhad is seeking an experienced MLOps Engineer to join the Credit Modelling & Data Management team in Malaysia. You will deploy, monitor, and maintain credit risk scorecard models in production, ensuring stability, audit-readiness and reliable operation.

Focus areas include data pipelines for scorecard inputs, CI/CD support, model versioning, and monitoring of DataRobot and AWS SageMaker deployments.

Qualifications

• Bachelor's Degree in Computer Science, Data Analytics, Software Engineering, Information Systems or related discipline.
• Minimum 5 years of experience in MLOps, Machine Learning Platform Engineering or Model Deployment.
• Hands-on experience with DataRobot (or similar AutoML/MLOps platform).
• Experience with AWS (SageMaker, Redshift or equivalent cloud technologies).
• Strong SQL and data pipeline (ETL/ELT) experience.
• Knowledge of CI/CD, model versioning and production deployment.

Responsibilities

• Deploy, monitor, and maintain credit risk scorecard models in production.
• Design, build, and maintain scalable pipelines that prepare/refresh scorecard inputs from source systems into DataRobot & AWS SageMaker.
• Implement data quality checks and transformation logic to ensure input-data consistency with development-time data.
• Automate ETL/ELT workflows and monitor pipeline performance for timely score generation.
• Support CI/CD for scorecard releases and maintain deployment documentation.

Skills

DataRobot

AWS SageMaker

SQL

CI/CD

Model versioning

Production deployment

Education

Bachelor's Degree (CS/IS/Engineering)

Tools

DataRobot

AWS SageMaker

Job description

AEON Credit Service (M) Berhad is seeking an experienced MLOps Engineer to join the Credit Modelling & Data Management team in Malaysia. You will deploy, monitor, and maintain credit risk scorecard models in production, ensuring stability, audit-readiness and reliable operation.

Focus areas include data pipelines for scorecard inputs, CI/CD support, model versioning, and monitoring of DataRobot and AWS SageMaker deployments.