Description

Design end-to-end MLOps architectures that align machine learning capabilities with business objectives.

This role is on-site.

Responsibilities

• Design scalable, secure, and reliable end-to-end MLOps pipelines with modular CI/CD architectures.
• Translate business requirements into scalable machine learning solutions and serve as the technical liaison between MLOps teams and business units.
• Facilitate the transition of models from development to production and define MLOps standards for compliance and regulatory adherence.
• Develop deployment strategies for ML models as APIs, batch processing jobs, or streaming services.

Required Skills

• 5+ years of experience in solution architecture, MLOps, or ML architecture roles.
• Proven expertise designing MLOps pipelines and managing the model lifecycle.
• Proficiency with ML orchestration and monitoring tools such as Kubeflow, MLflow, TensorFlow, or SageMaker.
• Ability to design observability frameworks for model performance and automated re-deployment.
• Mandatory fluency in Dutch.
• Bachelor's degree or equivalent graduate-level education.

Key Skills

Education

Any Graduate