MLOps Engineer – Credit Risk and Fraud Platform (Banking)
Location not identified
- Pay
- Pay not listed
- Work setting
RemoteLocation limits apply — work setting source
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.
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingBuild and maintain CI/CD pipelines for machine learning models
Manage model versioning, promotion, and rollback processes
Deploy and operate LangChain and LangGraph services in production
Implement monitoring for model performance, drift, and runtime failures
Ensure traceability, auditability, and compliance readiness
From the employer’s posting
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
What you’ll bring
All qualificationsCore experience
- Strong hands-on experience in MLOps or ML platform engineering
- Solid Python skills for automation and tooling
- Production experience with Docker and Kubernetes
- Practical experience with MLflow or similar lifecycle tools
- Experience with Azure or AWS cloud platforms
Qualification wording
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
Experience working with Azure or AWS cloud platforms
Tools in this posting
- Python
- AWS
- Azure
- Docker
- Kubernetes
- MLflow
Source — Tool mentions in context
- 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
- Hands on experience with CI/CD pipelines - Experience working with Azure or AWS cloud platforms - Understanding of monitoring and observability for ML systems
- 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
- 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
Benefits in the posting
Full benefits wording- Comprehensive healthcare
- Remote work model
From the employer’s posting.
Posting record
Report an errorOpen 4 monthsWe first saw this posting 149 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 3, 2026 · 149 days ago
- Recorded sightings
- 195
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Location not supplied.
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.
More source context
- Long-term B2B contract with a stable project pipeline - Remote work model
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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