MLOps Engineer – Credit Risk and Fraud Platform (Banking)
Posted 4 hours ago
Worldwide
⭐
5-10 years experience
Please mention DailyRemote when applying
AI Summary
Build and maintain CI/CD pipelines and operationalize the model lifecycle for a credit risk and fraud platform. Deploy and monitor GenAI services using LangChain and LangGraph while ensuring regulatory compliance and system reliability.
This is a remote position.
We are looking for an MLOps Engineer to join a large scale decision intelligence platform supporting credit risk assessment and fraud prevention within an international banking environment. The platform combines advanced machine learning, high volume data processing, and GenAI orchestration layers embedded directly into live banking systems. This is a production critical role focused on operational excellence, reliability, and regulatory alignment. The system is already live and continuously evolving, with frequent model releases, new data integrations, and LangChain and LangGraph based reasoning components layered on top of core ML outputs.
Responsibilities
Responsibilities
- Build and maintain CI/CD pipelines for machine learning models
- Operationalise model lifecycle processes including versioning, promotion, and rollback
- Deploy and operate LangChain and LangGraph based services in production
- Implement monitoring for model performance, drift detection, and runtime failures
- Ensure traceability, auditability, and compliance readiness in regulated environments
- Collaborate with data scientists and ML engineers to support smooth model releases
- Optimise reliability, scalability, and security of ML and GenAI workloads
Requirements
- Strong hands on experience in MLOps or ML platform engineering
- Solid Python skills for automation and tooling
- Experience with Docker and Kubernetes in production environments
- Practical experience with MLflow or similar model lifecycle management tools
- Hands on experience with CI/CD pipelines
- Experience working with Azure or AWS cloud platforms
- Understanding of monitoring and observability for ML systems
- Ability to operate in regulated or compliance heavy environments
- Fluent English for professional collaboration
Nice to have
- Experience deploying LangChain or LangGraph based services
- Exposure to banking, fintech, or fraud detection systems
- Experience with model governance and regulatory documentation
- Familiarity with high availability and low latency systems
Benefits
- Solid, competitive salary
- Work in a multinational environment on international projects
- Comprehensive healthcare
- Long-term B2B contract with a stable project pipeline
- Remote work model
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