DevOps Engineer - ML

In your role, you will support the development of our internal ML tooling for large image analysis in the medical domain. Furthermore you will be working towards productization of prototypic workflows into compliant ML products at scale.

• Support development of internal ML tooling
• Develop novel or improve existing tools
• Add new features, fix bugs, raise test coverage and improve documentation
• Develop, deploy and maintain complex data stream pipelines
• Evaluate, qualify and integrate cloud-based computing platforms in close collaboration with IT and development teams
• Help define workflows, evaluate tooling and infrastructure, and aid users in test scenarios
• Ensure compliance of processes and developed tooling

Must-have Skills or Experiences

• Experience building and applying ML (not hosted LLM) systems with frameworks such as PyTorch, TensorFlow, JAX
• Experience building training data processing pipelines for image data
• Experience in MLOps lifecycles (model training, validation, deployment, quality monitoring). Similar experience with other data types such as proteomics is also considered
• Python (excellent, required)
• Experience with MLOps tools (W&B, MLFlow) and deep learning frameworks (PyTorch, PyTorch Lightning, etc.)
• Strong software engineering best practices: writing high-performance, modern, bug-free code with proper documentation, unit testing, code quality, etc. (required)
• Good working knowledge of Linux environments, Git-based workflows, GitHub Actions, containerization (Docker) and orchestration (Kubernetes)
• At least several years of experience as DevOps