Senior Machine Learning Engineer

• Design, build, and maintain our Databricks-based ML platform: packages, notebook templates, CI/CD pipelines, and self-service tooling 

• Collaborate with value streams and other departments: advise, train, and provide hands-on support to set up and productionize new ML models 

• Set up and manage end-to-end MLOps workflows using tools like MLflow 

• Implement cost-tracking and reporting dashboards for Databricks usage 

• Monitor platform performance, scalability, and security—and continuously drive improvements 

• Mentor junior colleagues and team members, helping define best practices and standards 

• You hold a Master’s degree (or higher) in Computer Science, Artificial Intelligence, or a related field 

• At least 5 years of relevant experience as an ML Engineer or Data Engineer with a strong Data Science affinity in a data-driven environment 

• Extensive (3+ years) hands-on experience with Databricks 

• Excellent programming skills in Python and proficiency with SQL and PySpark 

• Experience with cloud platforms, preferably Azure 

• Deep knowledge of MLOps tooling: MLflow and CI/CD (Git) 

• Strong communication skills in English; you can influence both technical and non-technical audiences 

• A proactive, solution-oriented mindset and the ability to drive change in others 

• Co-defining and executing the roadmap (OKRs) for our ML platform 

• Enabling self-service for data scientists: reducing operational overhead so they can focus on model development 

• Ensuring a stable, secure, and cost-efficient Databricks environment 

• Conducting quality and code reviews, and coaching colleagues 

• Documenting and evangelizing platform standards and best practices across the organization 

You will work in Eneco’s new Tech department, in the ML Engineering discipline. Eneco has adopted a matrix organisational structure for our product portfolio. As a Senior ML Engineer, you will be embedded in one of our product teams or one of our technical platform teams. While your main focus will be to provide value for these products or platforms, you will also work together with fellow data professionals to build a community of practice around ML Engineering.