Fraud ML Engineer — Real-Time Scoring & MLOps

GBG Malaysia; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

GBG Malaysia is seeking a Machine Learning Engineer to advance ML capabilities within Global Fraud Solutions. You will collaborate with Software Engineering, Product and Data Scientist teams to deliver the ML roadmap and build robust MLOps pipelines that support real-world fraud detection challenges faced by banking and fintech customers globally.

You will apply your expertise in machine learning to real-world fraud and AML use cases, optimizing latency and accuracy for batch and real-time

Qualifications

• 3+ years building and deploying production ML systems in Python.
• Experience with cloud-native ML platforms and containerisation.
• Eligible to work in Malaysia.

Responsibilities

• Design, develop, and deploy ML models for fraud and AML detection, supporting both batch and real-time transaction scoring scenarios.
• Build and maintain MLOps pipelines covering model training, validation, deployment, monitoring, and retraining workflows using modern tooling (e.g. MLflow, Tecton, or equivalent feature stores).
• Collaborate with data engineers to design feature engineering pipelines and maintain the Predator feature dictionary and sync mechanisms.
• Optimise model performance to meet strict latency and TPS targets required for real-time fraud decisioning.
• Conduct model validation, A/B testing, permutation importance analysis, and champion/challenger evaluations to ensure model quality.
• Work with the Architecture Review Committee (ARC) to align ML platform choices with the overall modernization architecture.
• Stay current with advances in fraud detection ML — including graph-based models, anomaly detection, and generative AI applications — and propose relevant adoptions.
• Mentor junior team members and contribute to knowledge sharing across squads.

Skills

Python (ML)

Cloud platforms

Containerisation

CI/CD for ML

Fraud/AML modeling

Malaysia work eligibility

Tools

Docker

Kubernetes

AWS SageMaker

Azure ML

GCP Vertex AI

Job description

GBG Malaysia is seeking a Machine Learning Engineer to advance ML capabilities within Global Fraud Solutions. You will collaborate with Software Engineering, Product and Data Scientist teams to deliver the ML roadmap and build robust MLOps pipelines that support real-world fraud detection challenges faced by banking and fintech customers globally.

You will apply your expertise in machine learning to real-world fraud and AML use cases, optimizing latency and accuracy for batch and real-time