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
Basic qualifications
- 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
Preferred qualifications
- 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
Tags & focus areas
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