Educational Content Author

Educational Content Author - Cloud Solution Architect Nebius is seeking a Middle AI Solution Architect to drive adoption of our high-performance cloud infrastructure by creating educational content. You’ll join our Nebius Academy team with a mission to help developers succeed with Nebius’ cloud offerings. In this role, you’ll focus on communicating technical capabilities and showcasing differences across Nebius products: cloud infrastructure services and Token Factory. This unique role combines some responsibilities of an AI Solution Architect and an Educational Content Author, allowing you to develop skills and grow in different directions as a Solution Architect and/or Developer Advocate while working together with an amazing team of Nebius AI Engineers and Solution Architects. Your responsibilities will include: Educational content creation Create technical content demonstrating how to effectively use computing workloads with VMs, GPU clusters, k8s, SLURM, Soperator, etc. Develop sample code, tutorials, and reference architectures showcasing best practices for cloud computing and ML infrastructure Create video tutorials and live coding sessions demonstrating effective use of Nebius cloud infrastructure Helping Academy's partners build cloud solutions Collaborate with academic partners (universities, e.g., Stevens, MIT) to understand their requirements and develop solution architectures that align with their needs: design and document Infrastructure as Code solutions, documentation, and technical how-to guides in collaboration with the Nebius Solutions Architect Team Act as a trusted advisor to our academic partners, providing technical expertise on GPU cloud technologies and best practices We expect you to have: Technical knowledge and skills Strong understanding of cloud infrastructure and distributed computing principles Experience with virtual machines, containerization, and managing compute resources Experience building with IaC solutions, preferably Terraform Knowledge of GPU clusters and techniques for optimizing ML workloads Working knowledge of container orchestration systems like Kubernetes and job schedulers like SLURM Familiarity with infrastructure components including networking, storage optimization, and resource management Experience optimizing performance of diverse workloads in cloud environments Strong programming skills, particularly in Python, and familiarity with the PyTorch ecosystem Understanding of cloud infrastructure concepts and deployment patterns Excellent written communication skills and ability to clearly express technical ideas in text Practical experience 2+ years of experience in software development, cloud engineering, DevOps, or a similar technical role Demonstrated experience with cloud technologies and infrastructure Previous work with infrastructure-as-code, containerization, and cloud environments It will be an added bonus if you have Experience with MLflow, Apache Airflow, or Kubeflow Familiarity with cloud ML platforms like AWS, GCP, Azure ML, or NVIDIA NGC Experience managing hybrid cloud or on-prem GPU infrastructure Background working with technology partners and integrating third-party solutions Public presentation skills