AI/ML Specialist Solution Architect (Early Talent)

Summary:

Location: Remote from USA
Duration: 3 months
Compensation: Paid
Eligibility: Current University student (Computer Science or related field), Recent Graduate or Early Career specialist
Work authorization: permitted to work in the job’s location

Why work at Nebius
Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400+ employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

The role

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.

We expect you to have:

• 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.

Nice to have:

• 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.

Tools you may learn and use:

• Programming: Python (plus exposure to Go, Java, or C++).
• ML Frameworks: PyTorch, TensorFlow, JAX, Hugging Face.
• Infrastructure & DevOps: Docker, Git, Kubernetes, Terraform.
• Schedulers & Orchestration: Kubernetes, Slurm (learning-focused).

What we offer

• Competitive salary (ranging from 6,600 to 10,260 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.

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!