Kubeflow Jobs in Austria

In this role, you design AI solution architectures, develop data pipelines, implement MLOps, and embed trustworthy AI principles into systems to create robust, scalable applications.

In this role, you will implement models and data pipelines for AI projects, develop MLOps templates, and support the operation of CI/CD and monitoring systems in HPC environments.

You strategically develop the AI service catalog, manage MLOps automation, and enhance data pipelines while advising users in practical workshops and training on utilizing AI solutions.

In this role, you administer and optimize an on-premises cloud based on OpenStack, operate effective Kubernetes environments, and develop deployment pipelines to ensure system availability.

In this role, you provide technical support for partner projects, develop ML models and pipelines, operate CI/CD systems, and implement trustworthy AI practices in hybrid cloud environments.

In this role, you develop AI services, operate and improve MLOps stacks, implement documentation and SLAs, support partner projects, and organize workshops to increase the usage of AI services.

In this role, you will design comprehensive AI solutions, develop reference architectures, and ensure seamless integration of AI services in hybrid cloud environments while considering trustworthy AI principles.

In this role, you will develop strategic AI services and implement MLOps processes while supporting partner projects and conducting training to enhance AI application usage.

In this role, you design end-to-end AI solutions focusing on architecture, model development, and MLOps. You integrate AI services into hybrid cloud environments while ensuring scalability and trustworthy system design.

In this role, you provide technical support for partner projects, work on implementing data pipelines and CI/CD systems, and develop efficient AI models and workflows in HPC and hybrid cloud environments.

In this role, you will build a scalable software infrastructure for HPC and AI applications, conduct analyses, and optimize the entire AI/ML model lifecycle while implementing MLOps solutions.

You will develop and operate the ML platform for training and on-device deployment, build scalable data/training pipelines, and automate CI/CD, testing, quantization and packaging with Docker, Kubernetes and TensorFlow/PyTorch.