Aws Engineer (Python)

At Materialise Medical, we believe that better healthcare starts with solutions designed around the individual patient.If you’re passionate about bringing personalized care to every patient, you’ll love being a part of this team.Through the technology we develop, researchers, engineers, and clinicians are revolutionizing personalized treatment - helping improve and save lives daily.What you will do 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 Your profile Bachelor’s or Master’s degree in Computer Science, Data Engineering, Biomedical Engineering, or a related field Strong programming skills in Python Experience with machine learning frameworks such as TensorFlow, PyTorch, ONNX, or scikit-learn Proficiency in cloud platforms such as AWS SageMaker (preferred), GCP Vertex A,I or Azure ML Experience with medical imaging is a plus Knowledge of experiment tracking frameworks like mlflow or weights & biases Familiarity with Docker Familiarity with version control systems (e.G., Git, Git-LFS, DVS) and CI/CD pipelines Experience with Terraform Professional English language skills Solid knowledge of Linux and Windows operating systems #J-*****-Ljbffr

If you’re passionate about bringing personalized care to every patient, you’ll love being a part of this team. Through the technology we develop, researchers, engineers, and clinicians are revolutionizing personalized treatment - helping improve and save lives daily. What you will do 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 Your profile Bachelor’s or Master’s degree in Computer Science, Data Engineering, Biomedical Engineering, or a related field Strong programming skills in Python Experience with machine learning frameworks such as TensorFlow, PyTorch, ONNX, or scikit-learn Proficiency in cloud platforms such as AWS SageMaker (preferred), GCP Vertex A,I or Azure ML Experience with medical imaging is a plus Knowledge of experiment tracking frameworks like mlflow or weights & biases Familiarity with Docker Familiarity with version control systems (e.G., Git, Git-LFS, DVS) and CI/CD pipelines Experience with Terraform Professional English language skills Solid knowledge of Linux and Windows operating systems #J-*****-Ljbffr

At Materialise Medical, we believe that better healthcare starts with solutions designed around the individual patient.