Deploy ML/AI Models: Work with Data Scientists to deploy secure, scalable, and reliable models into production.
Build CI/CD Pipelines: Automate testing, packaging, and deployment for data and model workflows.
Manage Data Pipelines: Design and maintain efficient data flows across storage systems, databases, and platforms.
Set Up Environments: Manage dependencies, development environments, and tooling for smooth project onboarding.
Operate Kubernetes: Deploy and maintain containerized AI components using Kubernetes.
Monitor & Troubleshoot: Oversee model/application performance, resolve incidents, and conduct root-cause analyses.
Optimize & Innovate: Identify improvements, adopt new technologies, and enhance AI engineering practices.

Bachelor’s degree in Computer Science, Engineering, or related field
Strong background in programming, system engineering, or DevOps is highly valued
Strong proficiency in Python
Experience with REST APIs and Git
Hands-on expertise in CI/CD and MLOps/DevOps practices
Practical experience with Docker and Kubernetes
Familiarity with Linux, software testing, and modern software engineering workflows
Nice to have: SQL/PostgreSQL, MLflow, Helm, or related tooling
Collaborative and team-oriented mindset
Proactive, solution-driven, and comfortable working in dynamic environments
Strong communication, analytical, and problem-solving abilities
Fluent in English (spoken and written)
Knowledge of additional languages (Dutch or French) is a plus

A very competitive salary package including a company car, iPhone and different allowances
Extensive trainings in Belgium and Denmark on technical matters, as well as soft skills and project management
Access to new technologies and innovative equipment

Machine Learning Engineer

Key skills