N 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.
Your main tasks will include:
* 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
Your profile:
* Successfully completed degree in computer science, data science, or comparable field
* Experience in the development, implementation, and maintenance of ML systems, preferably in the pharmaceutical or life sciences industry
* Strong communication skills, persuasiveness, and ability to collaborate with a wide range of stakeholders
* Very good written and spoken German and English skills