MLOps Engineer – Portfolio Optimisation and Customer Analytics 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 support an enterprise analytics and optimisation platform within an international banking environment. The platform underpins pricing, capital allocation, and customer lifetime value decisions across multiple markets and product lines. It operates at scale with regular model retraining cycles and governed analytics processes. Analytical outputs feed both traditional reporting layers and LangChain and LangGraph based GenAI workflows that generate automated insights and scenario analysis. This role focuses on operationalising analytical models and ensuring stable, repeatable production workflows.
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 postingDesign and operate training and deployment pipelines for models
Automate model retraining, validation, and promotion processes
Ensure reproducibility across development, testing and production
Enable structured exposure of model outputs to LangChain and LangGraph workflows
Monitor performance, stability and reliability of ML pipelines
From the employer’s posting
Design and operate training and deployment pipelines for analytical and optimisation models
Automate model retraining, validation, and promotion processes
Ensure reproducibility and consistency across development, testing, and production environments
Enable structured exposure of model outputs to LangChain and LangGraph workflows
Monitor performance, stability, and reliability of ML pipelines
What you’ll bring
All qualificationsCore experience
- Strong experience in MLOps or ML platform engineering
- Experience integrating ML outputs with LangChain or LangGraph workflows
- Solid Python skills for automation and tooling
- Experience with optimisation models or large scale analytical platforms
- Hands on experience with Docker and Kubernetes
- Understanding of data governance and audit requirements
Qualification wording
Strong experience in MLOps or ML platform engineering
Experience integrating ML outputs with LangChain or LangGraph workflows
Solid Python skills for automation and tooling
Experience with optimisation models or large scale analytical platforms
Hands on experience with Docker and Kubernetes
Understanding of data governance and audit requirements
Tools in this posting
- Python
- Docker
- Kubernetes
- MLflow
- Airflow
Source — Tool mentions in context
- Strong experience in MLOps or ML platform engineering - Solid Python skills for automation and tooling - Hands on experience with Docker and Kubernetes
- Solid Python skills for automation and tooling - Hands on experience with Docker and Kubernetes - Practical experience with MLflow or similar model lifecycle management tools
- Hands on experience with Docker and Kubernetes - Practical experience with MLflow or similar model lifecycle management tools - Experience with workflow orchestration tools such as Airflow
- Practical experience with MLflow or similar model lifecycle management tools - Experience with workflow orchestration tools such as Airflow - 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.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on madiffpl.zohorecruit.com. The employer’s form will show what is required.
Already applied? Track this application
Job description
This is a remote position.
We are looking for an MLOps Engineer to support an enterprise analytics and optimisation platform within an international banking environment. The platform underpins pricing, capital allocation, and customer lifetime value decisions across multiple markets and product lines. It operates at scale with regular model retraining cycles and governed analytics processes. Analytical outputs feed both traditional reporting layers and LangChain and LangGraph based GenAI workflows that generate automated insights and scenario analysis. This role focuses on operationalising analytical models and ensuring stable, repeatable production workflows.
Responsibilities
Responsibilities
- Design and operate training and deployment pipelines for analytical and optimisation models
- Automate model retraining, validation, and promotion processes
- Ensure reproducibility and consistency across development, testing, and production environments
- Support scalable analytical workloads across cloud platforms
- Enable structured exposure of model outputs to LangChain and LangGraph workflows
- Monitor performance, stability, and reliability of ML pipelines
- Collaborate closely with data scientists and analytics teams to streamline experimentation to production
Requirements
- Strong experience in MLOps or ML platform engineering
- Solid Python skills for automation and tooling
- Hands on experience with Docker and Kubernetes
- Practical experience with MLflow or similar model lifecycle management tools
- Experience with workflow orchestration tools such as Airflow
- Hands on experience with CI/CD pipelines
- Experience working with cloud data platforms
- Strong understanding of reproducibility and environment management
- Fluent English for professional collaboration
Nice to have
- Experience integrating ML outputs with LangChain or LangGraph workflows
- Exposure to banking, finance, or regulated environments
- Experience with optimisation models or large scale analytical platforms
- Understanding of data governance and audit requirements
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 support an enterprise analytics and optimisation platform within an international banking environment. The platform underpins pricing, capital allocation, and customer lifetime value decisions across multiple markets and product lines. It operates at scale with regular model retraining cycles and governed analytics processes. Analytical outputs feed both traditional reporting layers and LangChain and LangGraph based GenAI workflows that generate automated insights and scenario analysis. This role focuses on operationalising analytical models and ensuring stable, repeatable production workflows.
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.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.