We are looking for a Machine Learning engineer for one of our clients in the financial sector. As a Machine Learning Engineer, you will design, build, and maintain frameworks to train, deploy, and monitor machine learning models in production. You will collaborate with data scientists and engineers, contribute to development best practices, and enhance our machine learning platform. You will work within an agile DevOps team responsible for end-to-end delivery of ML solutions.

Key Responsibilities

• Work in an Agile/Scrum DevOps team

• Build and maintain automated CI/CD pipelines (YAML)

• Collaborate with data scientists to train, deploy, and monitor models

• Implement model retraining, performance tracking, and drift detection

• Contribute to improving MLOps frameworks and tooling

• Write unit/integration tests and ensure high code quality

• Work with cloud technologies (primarily Azure)

Profile

• Bachelor's/Master's in Computer Science, AI, Software Engineering, or related field

• Experience deploying ML models into production

• Strong knowledge of MLOps principles and lifecycle management

• Experience with MLflow or similar platforms

• Solid Python programming skills

• Knowledge of CI/CD, monitoring, drift detection

• Familiarity with Azure DevOps and software engineering design patterns

• Experience with Azure, Azure Databricks, or other cloud platforms

• Knowledge of Spark ecosystem