Mid-Level MLOps Engineer (m/f/d)

As an MLOps Engineer at Redcare Pharmacy, you will build, operate, and enhance production ML/AI services. You join cross‑functional teams to turn models into reliable, secure production capabilities, driving observability and governance across the ML lifecycle. You’ll shape scalable infrastructure and CI/CD pipelines, enabling rapid model iteration and robust deployment. This role offers the chance to work at the intersection of data science and software engineering in a mission-driven, innovative environment.

• Work from Home up to 20 days a year within EU
• Team events and celebrations
• Professional mental health support via nilo
• Internal and external training for development
• Fully funded Deutschlandticket for commuting
• Urban Sports Club membership for health and wellbeing

• Build and manage containerized Python-based services on Kubernetes or similar platforms
• Troubleshoot production ML/AI services to improve reliability, performance, and cost-efficiency
• Develop maintainable, well-tested code for production services, automation, and internal tooling
• Enhance CI/CD pipelines for ML/AI services to support reliable testing, deployment, and model iteration
• Implement data and model versioning, validation, and observability across the ML lifecycle
• Contribute to technical designs, architecture decisions, and participate in code reviews
• Integrate automated security checks into delivery pipelines and adhere to secure DevOps practices

• Practical experience in MLOps, DevOps, platform engineering, or software engineering with deployment in production
• Solid Python software engineering skills including automated testing, version control, and code review
• Hands-on experience with Docker and Kubernetes
• Experience with CI/CD tools such as GitHub Actions or Jenkins
• Familiarity with ML lifecycle practices (packaging, versioning, validation, deployment, monitoring); experience with MLflow or Kubeflow is welcome
• Understanding of software architecture and secure software development and delivery practices

• Cross-functional collaboration
• Problem solving
• Communication
• Python
• Docker
• Kubernetes