[Hiring] AI/ML Specialist Solution Architect @Nebius

Role Description

Customer experience at Nebius AI Cloud focuses on helping customers successfully adopt and scale AI workloads. As an intern, you’ll support this mission by learning how real-world AI systems are designed, deployed, and optimized at GPU cloud scale. You’ll gain exposure to modern ML frameworks, large-scale GPU infrastructure (including NVIDIA Hopper, Blackwell and Grace Blackwell platforms), and the collaboration between customers, engineering, and product teams.

This role offers a strong learning environment with mentorship, minimal bureaucracy, and opportunities to develop both technical and communication skills.

We are looking for an AI/ML Solutions Architect Intern to support AI-focused customers using Nebius services. This is a learning-focused role designed for students or early-career candidates who are interested in AI infrastructure, cloud platforms, and applied machine learning.

You will work closely with experienced Solutions Architects, Engineers, and Product teams to help design, document, and support AI solutions.

Your responsibilities will include:

• Assist in designing and documenting AI and ML solutions.
• Learn how distributed training and inference workloads run on multi-GPU cloud-based systems.
• Help prepare technical materials such as presentations, documentation, tutorials, or demos.
• Participate in investigation, troubleshooting and optimization tasks under guidance from senior team members.

Qualifications

• Currently pursuing or recently completed a degree in Computer Science, Engineering, Data Science, or a related field.
• Solid understanding of machine learning concepts and workflows.
• Familiarity with at least one ML framework such as PyTorch, TensorFlow, or JAX.
• Comfort with programming in Python (other languages are a plus).
• Interest in cloud infrastructure, GPUs, and large-scale AI systems.
• Strong communication skills and a willingness to learn and ask questions.

Requirements

• Exposure to Kubernetes, Docker, or other container technologies.
• Familiarity with Git or basic DevOps workflows.
• Coursework or projects involving distributed systems, MLOps, or deep learning.
• Experience with AI projects from school, hackathons, or personal work.

Benefits

• Competitive salary (ranging from 8,160 – 12,240 USD) and comprehensive benefits package.
• Mentorship from experienced AI, ML, and cloud infrastructure professionals.
• Hands-on experience with real customer workloads and production systems.
• Remote work flexibility and a collaborative, supportive team environment.
• Opportunity to be considered for a full-time role after the Program.