Introduction
- 36 hours per week
- Start: ASAP
- End: 31-12-2026
- Extension is possible
- ZZP is not allowed
- Candidates must live in Netherlands at this moment
- Deadline: Monday 19-01-2026 at 10AM
Organization
Within Finance & Risk we starting up the AI / ML capability and we need an engineer who can help setting up this capability an lead the way true helping setting up a reg-AI solution next to bring our data engineers up to speed.
Function
As a Machine Learning Engineer, you will play a crucial role in designing, developing, and maintaining frameworks that are used to train and monitor Machine Learning models. You have a clear understanding on the latest technologies and best practices in bringing a machine learning model into production. You have an in-depth understanding of the Machine Learning lifecycle and how to apply it in practice. Your role will involve collaborating with cross-functional teams, ensuring high standard of code quality, and contributing to the continues improvement of our machine learning pipelines. This is an exciting opportunity to apply your expertise in Machine Learning and software engineering to contribute to the development of innovative solutions.
With the following results
You will be part of a DevOps team so Development and Ops activities will go hand in hand
Working with Azure/ Databricks tools and technologies
Building automated YAML pipelines towards production
Collaborate with data scientists, software engineers, and domain experts to understand project requirements and translate them into technical specifications
Collaborate with data scientists to train and maintain deployed models, tracking their performance and making necessary adjustments to ensure accuracy and reliability
Work with other ML engineers to optimize our MLOps frameworks
Design and implement unit test, integration tests, and code reviews to ensure code quality and reliability
Requirements
With the following results
You will be part of a DevOps team so Development and Ops activities will go hand in hand
Working with Azure/ Databricks tools and technologies
Building automated YAML pipelines towards production
Collaborate with data scientists, software engineers, and domain experts to understand project requirements and translate them into technical specifications
Collaborate with data scientists to train and maintain deployed models, tracking their performance and making necessary adjustments to ensure accuracy and reliability
Work with other ML engineers to optimize our MLOps frameworks
Design and implement unit test, integration tests, and code reviews to ensure code quality and reliability
Relevant knowledge, skills, competences & desired education level
Bachelor’s or master’s degree in Computer Science / AI / Software Engineering or similar technical fields
Experience with productionalizing Machine Learning models
Experience with MLOps principles and striving to apply them in your day-to-day work
Experience with MLflow or any other Machine Learning lifecycle platforms
Experience with model training, re-training, evaluation and monitoring
Knowledge of data and model drift detection
Experience with building CI/CD pipelines
Excellent in analytical thinking
Strong programming skills in Python
Creative and problem-solving mindset, proactive and ready to be challenged
Excellent communication skills with different stakeholders
You are a team player and eager to share your expertise with your team
Familiarity with Azure DevOps
Familiarity with software engineering design patterns
Good to have:
• Knowledge of Azure Databricks
• Experience with Microsoft Azure
• Familiarity with Spark ecosystem is a plus
Extra information:
We are looking for more developer centric profiles, last time we got a lot of team lead like CV’s, we want more Machine Learning engineers who do hands-on development. I think this summarizes the feedback also received from other interviewers looking at the CV’s provided.
Information
Sean Verhoef +31(0)20-3337629
Application
Sean Verhoef +31(0)20-3337629