Description

You will build and manage enterprise-scale fraud detection platforms, focusing on scalable ML deployment, automated releases, and production reliability.

This role is on-site.

Responsibilities

• Design and implement enterprise MLOps platforms, including model registries and automated release pipelines.
• Automate model deployment, rollback mechanisms, and inference infrastructure.
• Establish end-to-end monitoring, alerting, and observability for fraud detection systems.
• Ensure platform reliability, scalability, and governance through rigorous audit controls.

Required Skills

• 8+ years of experience in MLOps, DevOps, or SRE.
• Strong proficiency with Google Cloud Platform (GCP).
• Experience with Kubernetes and infrastructure automation.
• Knowledge of Agentic AI architecture and CI/CD for ML.
• Ability to design scalable model deployment frameworks.
• Understanding of security controls and compliance in ML systems.
• Experience with monitoring and observability tools.

Preferred Skills

• Background in feature store management.
• Experience with data engineering for ML pipelines.

Key Skills

Education

Any Graduate