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

Your tasks

• As an AI/ML Engineer, you design and implement AI/ML pipelines – this includes data ingestion, model training, and deployment – for hybrid cloud/on-prem and edge environments
• You containerise AI applications, working closely with our AI/ML engineers, using technologies like Docker and Podman. You deploy models to both cloud and on-prem infrastructure, such as Kubernetes and Azure
• You optimise our AI models specifically for air-gapped and low-power systems. You ensure a secure model deployment, always adhering to MLOps best practices like ISO 42001
• You optimise model performance – focusing on latency and accuracy – and monitor them in production environments through logging and A/B testing, specifically for edge and hybrid deployments
• You collaborate with the pre-development team, refining prototypes for edge AI and constrained environments. You ensure reproducibility and scalability utilising MLOps tools like MLflow, and edge-specific frameworks

Your qualifications

• You hold a BS/MSc degree in Computer Science, Software Engineering, Electrical Engineering, or a related field
• You demonstrate practical MLOps engineering skills equivalent working in product-ready environments
• You demonstrate proven experience with hybrid cloud/on-prem deployment strategies (e.g., Azure, Kubernetes, Docker)
• You have experience deploying models in air-gapped and power-constrained environments (e.g., edge devices, embedded systems)
• You are proficient in Python, cloud platforms, and containerization (Docker, Kubernetes, GitOps)
• You possess strong knowledge of ML pipelines and CI/CD workflows
• You are familiar with edge AI tools (e.g., TensorFlow Lite, ONNX)
• You have a DevOps mindset with a focus on automation and reliability
• You are able to troubleshoot both model and infrastructure issues
• Fluent English is required; German language skills are a plus

Interested?