MLOps Engineer – Portfolio Optimisation and Customer Analytics Platform (Banking

Descrição da Vaga

Requisitos

• 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
• 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

Responsabilidades

• 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
• 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

Benefícios