Senior MLOps / DevOps Engineer AI (Computer Vision) (m/f/d)

Development & operation: You design, implement and maintain software solutions as well as cloud infrastructures for the training, management and deployment of computer vision data sets and models. Pipeline optimization: You unleash and optimate deployment pipelines to allow seamless integration and scaling of machine learning models. Teamwork: You work closely with our AI Engineers to make the development, training and deployment of AI models more efficient. ML pipelines: You develop and manage ML pipelines and make sure that You run stable in production environments through clean software engineering. Infrastructure & scaling: You contribute to building a robust, safe and high-performance infrastructure for our AI solutions on a large scale.

Experience & Foundation: You have a solid base in software engineering and machine learning. You bring at least 3 years of professional experience in MLOps, DevOps or Data Engineering. Python expert: You master Python running and have a passion for clean, wartable and well-tested code. In the best case, you already have experience with the ML-Library PyTorch. Infrastructure professionals: You are safe in dealing with Docker and Kubernetes and master infrastructure as code with Terraform. Cloud natives: You have practical experience with at least one large cloud provider (AWS, GCP or Azure) as well as in building and managing CI/CD pipelines. ML Interest: You have a basic understanding of deep learning and AI workflows. Ideally, you have already worked with MLOps tools like MLflow, Kubeflow or Cloud solutions like SageMaker/Vertex AI. Monitoring Mindset: You have experience with monitoring and observability stacks (e.g. Prometheus, Loki, Grafana) and understand DevOps principles. Macher mentality: Complex technical challenges solve you proactively, reliably and independently with pragmatic, scalable solutions. .