Educational Content Author - Cloud Solution Architect, Nebius Academy

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Educational Content Author – Cloud Solution Architect, Nebius Academy based in Ireland. This role combines cloud solution architecture, technical education, and developer-focused content creation in a rapidly evolving AI infrastructure environment. You will help developers and academic partners understand and effectively use advanced cloud computing and ML infrastructure technologies. Your work will span hands-on tutorials, sample code, reference architectures, video content, and live technical sessions. You will also collaborate with universities and technical partners to design practical cloud solutions tailored to their requirements. The role offers exposure to GPUs, Kubernetes, distributed computing, infrastructure as code, and modern AI/ML workloads. You will work closely with experienced engineers and solution architects while developing your own expertise across architecture and developer advocacy. This is an opportunity to turn complex infrastructure concepts into clear, practical learning experiences that accelerate adoption and technical success. Create high-quality educational content demonstrating how to effectively use cloud computing workloads, including virtual machines, GPU clusters, Kubernetes, SLURM, Soperator, and related technologies. Develop practical sample code, tutorials, technical guides, and reference architectures that demonstrate cloud and ML infrastructure best practices. Produce video tutorials and participate in live coding sessions to make complex technical concepts accessible to developers and technical audiences. Work with academic partners, including universities, to understand their technical requirements and translate them into appropriate cloud solution architectures. Collaborate with solution architecture and engineering teams to design and document Infrastructure as Code solutions, technical documentation, and implementation guides. Act as a trusted technical advisor to academic partners, providing guidance on GPU cloud technologies, infrastructure design, and best practices. Help communicate the capabilities and differentiators of cloud infrastructure services and AI-related platforms to technical audiences. Design practical deployment patterns and solutions that address real-world compute, storage, networking, and ML workload requirements. Optimize cloud workloads and architectures for performance, efficiency, scalability, and reliability. Translate complex infrastructure and AI concepts into clear, accurate, and engaging written and visual learning materials. Stay current with developments in cloud infrastructure, distributed computing, GPU technologies, container orchestration, and machine learning platforms. Contribute technical insights and practical experience to the broader Academy, engineering, and solution architecture communities. Requirements: 2+ years of professional experience in software development, cloud engineering, DevOps, solution architecture, or a closely related technical field. Strong understanding of cloud infrastructure and distributed computing principles. Hands-on experience with virtual machines, containerization, and managing compute resources in cloud environments. Practical experience building Infrastructure as Code solutions, preferably using Terraform. Knowledge of GPU clusters and techniques for optimizing machine learning workloads. Working knowledge of Kubernetes and job schedulers such as SLURM. Familiarity with infrastructure components including networking, storage optimization, resource management, and deployment patterns. Experience optimizing the performance of diverse workloads in cloud environments. Strong programming skills, particularly in Python, with familiarity with the PyTorch ecosystem. Excellent written communication skills and the ability to explain sophisticated technical concepts clearly and effectively.