Offer summary

Qualifications:

5–10+ years experience in ML engineering or MLOps., 3+ years in professional services or technical consulting roles., Strong proficiency in Python with experience in PyTorch or TensorFlow., Proven success deploying ML models to production at scale..

Key responsibilities:

Deliver AI Professional Services including model training, fine-tuning, and inference optimization.

Integrate Nebius AI solutions into diverse client environments.

Design and set up scalable ML training and inference workflows on GPU clusters.

Automate MLOps pipelines and manage the entire model lifecycle.

Job description

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 work
Headquartered 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 800 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’re looking for a hands-on AI Engineer to join our Professional Services team. You will deliver GPU-powered AI/ML solutions for enterprise clients, focusing on implementation, integration, and optimization of production-grade systems.

You’re welcome to work remotely in the US.

Your responsibilities will include:

Deliver AI Professional Services including model training, fine-tuning, and inference optimization
Integrate Nebius AI solutions into diverse client environments
Design and set up scalable ML training and inference workflows on GPU clusters
Automate MLOps pipelines and manage the entire model lifecycle
Develop clear architecture documentation and operational guides
Lead technical efforts during service delivery engagements
Contribute to internal tooling, frameworks, and best practices

We expect you to have:

5–10+ years experience in ML engineering or MLOps
3+ years in professional services or technical consulting roles
Strong proficiency in Python; hands-on experience with PyTorch or TensorFlow
Proven success deploying ML models to production at scale
Skilled with Kubernetes, Docker, Terraform, and CI/CD pipelines
Good understanding of the GPU stack: CUDA, drivers, and relevant libraries
Excellent communication skills; comfortable working independently with clients
Fluent in English

It will be an added bonus if you have:

Experience with MLflow, Apache Airflow, or Kubeflow
Familiarity with cloud ML platforms like AWS, GCP, Azure ML, or NVIDIA NGC
Experience managing hybrid cloud or on-prem GPU infrastructure
Background working with technology partners and integrating third-party solutions

What we offer

Competitive salary and comprehensive benefits package.
Opportunities for professional growth within Nebius.
Hybrid working arrangements.
A dynamic and collaborative work environment that values initiative and innovation.

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!

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