Educational Content Author - Cloud Solution Architect, Nebius Academy

Accountabilities

• • 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.
  • Demonstrated ability to create technical documentation, tutorials, examples, or other educational materials.
  • Strong problem-solving skills and the ability to approach complex infrastructure challenges in a structured way.
  • Ability to collaborate effectively with engineers, solution architects, academic partners, and other technical stakeholders.
  • Experience with MLflow, Apache Airflow, or Kubeflow is an advantage.
  • Familiarity with cloud ML platforms such as AWS, GCP, Azure ML, or NVIDIA NGC is a plus.
  • Experience managing hybrid cloud or on-premises GPU infrastructure is desirable.
  • Experience working with technology partners or integrating third-party solutions is an advantage.
  • Public speaking or technical presentation experience is a plus.
  • Authorization to work in the country where you are based, without requiring employment sponsorship.

  Benefits:

  • Competitive compensation.
  • Remote working flexibility and significant ownership over your work.
  • Career growth and continuous learning opportunities.
  • Opportunity to develop expertise across cloud architecture, AI infrastructure, technical education, and developer advocacy.
  • Exposure to impactful AI and cloud infrastructure projects.
  • Collaboration with highly skilled engineers, solution architects, and technical professionals.
  • International working environment with diverse teams and perspectives.
  • Opportunity to work with academic and technology partners on real-world cloud solutions.
  • Fast-moving environment that encourages innovation, experimentation, and bold thinking.
  • Meaningful opportunity to contribute to the development of modern AI infrastructure and technical education.