MLOps Engineer: Scale Production ML for Healthcare

Mondeadditif; Heverlee; Sur place; EUR 65 000 - 90 000; Plein temps

Résumé du poste

Materialise Medical seeks an experienced MLOps/DevOps engineer to transform PoC scripts into production pipelines and maintain robust infra for model training, testing, deployment, and monitoring. You will collaborate with research and development teams to optimize performance and reliability in production environments.

The role requires strong Python, Docker, and cloud experience, with a bias toward MLflow or weights & biases, and familiarity with Terraform.

Qualifications

• At least 3 years of experience in an MLOps or DevOps role.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Biomedical Engineering, or a related field.
• Strong programming skills in Python.
• Experience with ML frameworks such as TensorFlow, PyTorch, ONNX, or scikit-learn.
• Proficiency with cloud platforms like AWS SageMaker, GCP Vertex AI, or Azure ML.
• Knowledge of experiment tracking frameworks like mlflow or weights & biases.
• Familiarity with Docker, ECR & EKS.
• Strong knowledge of Git, Git-LFS, DVC and CI/CD pipelines.
• Experience with Terraform.
• Professional English language skills.
• Solid knowledge of Linux and Windows operating systems.
• Experience with medical imaging is a plus.

Responsabilités

• Transform proof-of-concept scripts into Pipelines with different processing steps.
• Develop and maintain monitoring and alerting systems to ensure the health and performance of deployed models.
• Cross-functional collaboration with research teams and development teams.
• Maintain scalable, robust, and reliable infrastructure for model training, testing, deployment, and monitoring.
• Optimize and enhance model performance, scalability, and reliability in production environments.
• Take responsibility for code testing and quality checking.
• Stay on top of the latest trends in the field of MLOps and cloud platforms.

Connaissances

Python

MLOps

English proficiency

Linux/Windows

Formation

Bachelor’s or Master’s degree in CS/Data/Biomedical Engineering

Outils

Docker

Terraform

Git

MLflow

Weights & Biases

ECR

EKS

Description du poste

Materialise Medical seeks an experienced MLOps/DevOps engineer to transform PoC scripts into production pipelines and maintain robust infra for model training, testing, deployment, and monitoring. You will collaborate with research and development teams to optimize performance and reliability in production environments.

The role requires strong Python, Docker, and cloud experience, with a bias toward MLflow or weights & biases, and familiarity with Terraform.