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MLOps Engineer – Portfolio Optimisation and Customer Analytics Platform (Banking
JOB SUMMARY
Job details
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 al
location
, 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. ResponsibilitiesDesign and operate training and deployment pipelines for analytical and optimisation modelsAutomate model retraining, validation, and promotion processesEnsure reproducibility and consistency across development, testing, and production environmentsSupport scalable analytical workloads across cloud platformsEnable structured exposure of model outputs to LangChain and LangGraph workflowsMonitor performance, stability, and reliability of ML pipelinesCollaborate closely with data scientists and analytics teams to streamline experimentation to production
Requirements
Strong experience in MLOps or ML platform engineeringSolid Python skills for automation and toolingHands on experience with Docker and KubernetesPractical experience with MLflow or similar model lifecycle management toolsExperience with workflow orchestration tools such as AirflowHands on experience with CI/CD pipelinesExperience working with cloud data platformsStrong understanding of reproducibility and environment managementFluent English for professional collaborationNice to haveExperience integrating ML outputs with LangChain or LangGraph workflowsExposure to banking, finance, or regulated environmentsExperience with optimisation models or large scale analytical platformsUnderstanding of data governance and audit
requirements
Benefits
Solid, competitive salaryWork in a multinational environment on international projectsComprehensive healthcareLong-term B2B contract with a stable project pipelineRemote work model.
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 al
location
, 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. ResponsibilitiesDesign and operate training and deployment pipelines for analytical and optimisation modelsAutomate model retraining, validation, and promotion processesEnsure reproducibility and consistency across development, testing, and production environmentsSupport scalable analytical workloads across cloud platformsEnable structured exposure of model outputs to LangChain and LangGraph workflowsMonitor performance, stability, and reliability of ML pipelinesCollaborate closely with data scientists and analytics teams to streamline experimentation to production
Requirements
Strong experience in MLOps or ML platform engineeringSolid Python skills for automation and toolingHands on experience with Docker and KubernetesPractical experience with MLflow or similar model lifecycle management toolsExperience with workflow orchestration tools such as AirflowHands on experience with CI/CD pipelinesExperience working with cloud data platformsStrong understanding of reproducibility and environment managementFluent English for professional collaborationNice to haveExperience integrating ML outputs with LangChain or LangGraph workflowsExposure to banking, finance, or regulated environmentsExperience with optimisation models or large scale analytical platformsUnderstanding of data governance and audit
requirements
Benefits
Solid, competitive salaryWork in a multinational environment on international projectsComprehensive healthcareLong-term B2B contract with a stable project pipelineRemote work model.
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Madiff United States
