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Educational Content Author - Cloud Solution Architect, Nebius Academy
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Job Title: Educational Content Author – Cloud Solution Architect, Nebius Academy
Location: United Kingdom
About the Role
This role combines cloud solution architecture, technical education, and developer-focused content creation in a rapidly evolving AI infrastructure environment.
- Key Responsibilities:
- 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.
- Collaborate with universities and technical partners to design practical cloud solutions tailored to their requirements.
- Gain exposure to GPUs, Kubernetes, distributed computing, infrastructure as code, and modern AI/ML workloads.
- Work closely with experienced engineers and solution architects while developing your own expertise across architecture and developer advocacy.
- Turn complex infrastructure concepts into clear, practical learning experiences that accelerate adoption and technical success.
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.
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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.
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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.
How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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