AI ML Specialist Solutions Architect

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.

Where we workHeadquartered in Amsterdam and 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

We seek an experienced Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.

You’re welcome to work on-site in Amsterdam or remotely from any other EU country.

Your responsibilities will include:

• Designing customer-centric solutions that maximize business value and align with strategic goals.
• Building and maintaining long-term relationships to foster trust and ensure customer satisfaction.
• Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise.
• Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.

We expect you to have:

• 3+ years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or similar roles.
• Strong understanding of ML ecosystems, including models, use cases and tooling.
• Proven experience in setting up and optimizing distributed training pipelines across multi-node and multi-GPU environments.
• Hands-on knowledge of frameworks like PyTorch or JAX.
• Excellent verbal and written communication skills.

It will be an added bonus if you have:

• Expertise in deploying inference infrastructure for production workloads.
• Ability to transition ML pipelines from POC to scalable production systems.

Preferred tooling:

• Programming Languages – Python, Go, Java, C++
• Orchestration – Kubernetes (K8s), Slurm
• DevOps Tools – Git, Docker, Helm
• Infrastructure as Code (IaC) – Terraform
• ML Frameworks and Libraries – PyTorch, TensorFlow, JAX, HuggingFace, Scikit-learn

What we offer

• Competitive salary and comprehensive benefits package.
• Opportunities