Description

You will bridge the gap between data science MVPs and production-ready ML solutions by focusing on model optimization and scaling.

This role is on-site.

Responsibilities

• Refactor and optimize MVP models to move them from PoC phase to production deployment.
• Build and maintain resilient data pipelines for feature extraction, transformation, and model training.
• Develop APIs for model serving and integration with existing systems.
• Implement model retraining pipelines, versioning, and experiment tracking systems.
• Integrate LLMs into existing ML pipelines and applications.

Required Skills

• 5+ years of experience in machine learning engineering.
• Mandatory proficiency in Dutch.
• Experience transitioning models from PoC/MVP to production.
• Ability to build pipelines for both real-time and batch data processing.
• Knowledge of model explainability and fairness implementation.
• Experience with cloud environments including AWS and Azure.
• Ability to document model experiments, data versions, and technical decisions.
• Optimize model performance across AWS, Azure, and on-premises environments.

Preferred Skills

• Degree in any field (Any Graduate).

Key Skills

Education

Any Graduate