Overview
In the role of ML Ops Engineer, you will be responsible for developing, operating, and optimizing scalable ML infrastructures and processes across various phases of the pharmaceutical value chain. You will support data scientists in model implementation and help to deliver machine learning solutions securely, efficiently, and compliantly in complex enterprise environments.
Location and Employment
Location: Germany (Remote is fine)
Job Type: Contract
Responsibilities
- Collaborating with data scientists, IT teams, and specialist departments to deliver models that are ready for production and GxP-compliant
- Supporting MLOps frameworks and DevOps methods for the efficient rollout of new ML projects
- Performance monitoring and continuous optimization of productive ML systems
- Building and maintaining scalable machine learning pipelines (e.g., with AWS, Azure, GCP)
- Automating training, validation, and deployment steps for ML models
- Ensuring the reproducibility and traceability of model results
Seniority level
Employment type
Job function
Industries
- Pharmaceutical Manufacturing, Retail Pharmacies, and IT Services and IT Consulting
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