Materialise
Linkedin · Posted 8d ago
MLOps Engineer
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Indexed description
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
- 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
- Leuven, Belgium; Barcelona, Spain
- Full-time
- Hybrid
- Mid-senior level
- CV in English
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