Software Development : MLOps Engineer (f/m/d)

Your tasks

• Design and implement AI/ML pipelines (data ingestion, model training, deployment) for hybrid cloud/on-prem and edge environments.
• Containerise (e.g., Docker, Podman) AI applications in close contact with our AI/ML engineers.
• Deploy models to cloud and on-prem infrastructure (e.g., Kubernetes, Azure).
• Optimize our AI models for air-gapped and low-power systems.
• Ensure a secure model deployment adhering to MLOps best practices (e.g., ISO 42001)
• Optimize model performance (latency, accuracy) and monitor in production (logging, A/B testing) for edge and hybrid deployments.
• Collaborate with the pre-development team to refine prototypes for edge AI and constrained environments.
• Ensure reproducibility and scalability using MLOps tools (e.g., MLflow) and edge-specific frameworks.

Your qualifications

• BS / MSc in Computer Science, Software Engineering, Electrical Engineering or a related field.
• 3+ years of hands-on MLOps engineering experience in product ready environments.
• Proven experience with hybrid cloud/on-prem deployment strategies (e.g., Azure, Kubernetes, Docker).
• Experience deploying models in air-gapped and power-constrained environments (e.g., edge devices, embedded systems).
• Proficiency in Python, cloud platforms, and containerization (Docker, Kubernetes, GitOps).
• Strong knowledge of ML pipelines and CI/CD workflows.
• Familiarity with edge AI tools (e.g., TensorFlow Lite, ONNX).
• DevOps mindset with a focus on automation and reliability.
• Ability to troubleshoot both model and infrastructure issues.
• Fluent English required; German language skills are a plus.

Interested?