MLOps Engineer – Credit Risk and Fraud Platform (Banking)

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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.
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Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

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What you’ll work on

Full posting

Build 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 qualifications

Core 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

- 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

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Open 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: 194
Last seen by us: Oct 29, 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

View original posting ↗

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

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

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Source notes

Source excerpts

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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.

Open source at madiffpl.zohorecruit.com ↗Read the full description ↓

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