Machine Learning Engineer

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Jobalert

Machine Learning Engineer

• Analytics

• Hybride

Machine Learning Engineer

• Analytics

• Hybride

Machine Learning Engineer

• Analytics

• Hybride

Machine Learning Engineer

• Analytics

• Hybride

Bij ons werk je in een inspirerende omgeving waar samenwerking en groei centraal staan. We geloven in leren, elkaar versterken en met plezier resultaten behalen.

Lilian Hendrick, Hoofd Human Resources

Machine Learning Engineer

Step into a pivotal role within our ML Platform team, part of the Business Engine initiative - the backbone that empowers data scientists to move faster and smarter. We don't just build infrastructure; we architect the ML operating system for our company. And every day at work, you'll be doing your part for all the charities we support.

We're a tight-knit team of pragmatic problem-solvers who thrive on complex technical challenges and believe in pushing boundaries without breaking things. Whether it's fine-tuning a CI/CD pipeline, scaling models across regions, or introducing the next wave of MLOps tooling, we're always looking for bold engineers who love the details and see the big picture.

André Bloemenkamp, ML Engineer : "As a ML Engineer at the Lottery, you build scalable ML pipelines in close collaboration with data scientists. You work on impactful projects with room for innovation and growth."

What you'll do:

• Architect and manage cloud infrastructure using Terraform and AWS best practices (SageMaker, IAM, S3, etc.)
• Develop robust Python code to support the full ML lifecycle - from preprocessing to deployment orchestration.
• Design CI/CD pipelines in GitLab for automated model versioning, validation, packaging, and deployment to SageMaker.
• Deploy and monitor models using SageMaker Model Registry and Docker; automate alerts for drift, anomalies, and downtime.
• Enable platform adoption by building reusable patterns and onboarding teams to ML tooling and workflows.
• Promote engineering excellence through clean code, testing, type hints, linters, and strong documentation.
• Diagnose and resolve system issues, optimize performance, and improve scalability, observability, and cost efficiency.

You'd describe yourself as follows:

• At least 3-5 years in ML or MLOps focused on cloud-based, production systems, with solid understanding of deployment, monitoring, and model evaluation.
• Strong Python & SQL skills with a focus on clean, maintainable code
• Deep AWS expertise (SageMaker, S3, IAM, CloudWatch) and infrastructure as code using Terraform or similar.
• Hands-on CI/CD experience, ideally with GitLab, deploying real ML workloads.
• Proficient in Docker and container orchestration at scale.
• Continuous learner and team contributor, with a bias for sharing knowledge.
• A monthly salary indication between €5.000,- and €6.000,- based on a 40-hour week and flexible working hours.

Join us! We believe an inclusive organisation is the ideal breeding ground for creativity, collaboration and innovation. Employee solidarity is important to us, too. Each of us has a part to play in that - we are the organisation, after all. We strive to make everyone feel at home. That means keeping an open mind and paying attention to each other's welfare.

Can you see yourself as part of the team? We encourage you to apply - whatever your roots, religion, age, ability to work or life philosophy.

Please send your CV and cover letter (mandatory) to our through the link above.

Acquisition is not appreciated.

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