Responsibilities
- Automating everything related to the ML lifecycle to ensure efficiency and scalability.
- Using Infrastructure as Code (IaC) practices, such as Bicep, to manage and provision resources through code.
- Implementing best practices for continuous integration and delivery (CI/CD) pipelines, ensuring that ML models are reliably deployed to production environments.
- Collaborate with data scientists to deploy, monitor, and troubleshoot machine learning models and applications using Azure Machine Learning, Azure DevOps, and Azure AI Services.
- Challenge our existing security and reinforce our defenses.
Profile
- Master's degree in computer science, data science, engineering, or related field.
- At least 2 years of experience in data engineering, data science, or related roles.
- Proficient in Python.
- Experience with Azure cloud services and tools, notably Azure Machine Learning and Azure DevOps.
- Experience with MLOps concepts and frameworks.
- Knowledge on containerized deployment of ML products – e.g., Docker, Podman, Kubernetes.
- Excellent communication, collaboration, and problem-solving skills.
- Fluent in English is a must. Dutch and/or French is considered as a plus.
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