Machine Learning Engineer

Key Responsibilities:

• Financial Economic Crime (FEC) and Customer Due Diligence (CDD): Work on critical topics that significantly impact Rabobank s operations helping to prevent financial crimes and streamline processes for nonrisky customers.
  
• Azure Infrastructure Development: Develop manage and maintain highperformance machine learning and AI infrastructure on Azure.
  
• Collaboration: Work in a multidisciplinary team to develop scalable solutions and ML pipelines collaborating closely with teams and data scientists.
  
• System and Model Health: Ensure the health of systems and models by monitoring data quality performance and business impact and devising mitigation plans.
  
• Issue Identification: Identify underlying issues and opportunities across the ML development cycle introducing tools for efficient development and testing.
  
• Solution Implementation: Implement solutions in alignment with architectural guidelines collaborating effectively with your team.
  
• Continuous Learning: Stay up to date with the latest technologies to continuously evolve your craft.
  

Requirements

Required Skills:

• Education: A completed relevant HBO or WO education.
  
• Experience: Minimum 4 years of relevant experience in Software Data or ML Engineering with at least 2 years specifically in ML Engineering working with large data sets using Python and PySpark (experience with Azure Databricks is a plus).
  
• Software Development: Strong software development skills and good practices such as Git release management unit tests and testing strategies.
  
• Cloud Environment: Experience working in a cloud environment preferably Azure.
  
• Collaboration: Ability to collaborate with data scientists and machine learning practitioners to provide infrastructure support for model development and deployment.
  
• Analytical Skills: Strong analytical mind customeroriented driven and a true team player eager to learn new techniques and developments.