Fraud ML Engineer: Real-Time Risk & MLOps

GBG Plc; Kuala Lumpur; On-site; MYR 80,000 - 120,000; Full time

Job summary

GBG Plc in Kuala Lumpur is seeking a Machine Learning Engineer to advance ML capabilities within its Global Fraud Solutions team. You will collaborate with Software Engineering, Product, and Data Scientist teams on building MLOps pipelines and deploying models for fraud detection.

The ideal candidate will have at least 3 years of experience in production ML systems, strong knowledge of cloud-native platforms, and a focus on fraud detection and AML models. Join us to help create safe digital lives for genuine people.

Qualifications

• 3+ years building and deploying production ML systems in Python.
• Hands-on experience with CI/CD for ML pipelines.
• Experience with fraud detection and AML models.

Responsibilities

• Design, develop, and deploy machine learning models for fraud and AML detection.
• Build and maintain MLOps pipelines using modern tooling.
• Collaborate with data engineers on feature engineering pipelines.
• Optimise model performance for real-time fraud decisioning.
• Conduct model validation and A/B testing.
• Mentor junior team members.

Skills

Production ML systems in Python

Cloud-native ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)

Containerization (Docker, Kubernetes)

CI/CD for ML pipelines

Fraud detection and AML models

Job description

GBG Plc in Kuala Lumpur is seeking a Machine Learning Engineer to advance ML capabilities within its Global Fraud Solutions team. You will collaborate with Software Engineering, Product, and Data Scientist teams on building MLOps pipelines and deploying models for fraud detection.

The ideal candidate will have at least 3 years of experience in production ML systems, strong knowledge of cloud-native platforms, and a focus on fraud detection and AML models. Join us to help create safe digital lives for genuine people.