Nebius
Solutions Architect
Canada +1 · Full-time · Posted Oct 14, 2026
- Location
- Canada
United States - Experience
- 5+ years in customer-facing technical pre-sales; 5+ years with Infrastructure as Code; 5+ years with Kubernetes; 5 years developing Python-based solutions. Preferred: 3+ years with GPU computing.
- Education
- Bachelor's degree or foreign equivalent in a related field, or an equivalent combination of education and relevant experience.
- Visa sponsorship
- Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility as a condition of hire.
About the job
Designs cloud infrastructure and MLOps solutions for customers, advising them on architecture and helping optimize AI/ML pipelines on Nebius AI Cloud.
What you'll do
- Advise customers and deliver proof-of-concepts, workshops, presentations, and training on GPU cloud technologies.
- Translate customer requirements into solution architectures and document Infrastructure as Code solutions and technical guidance.
- Optimize customer pipeline performance and scalability, and coordinate customer scenarios with internal teams.
What they ask for
- Bachelor's degree or foreign equivalent in a related field, or an equivalent combination of education and relevant experience.
- 5+ years of customer-facing technical pre-sales experience, with pre-sales as a primary responsibility.
- 5+ years of experience with Infrastructure as Code for cloud infrastructure and network architectures.
- 5+ years of Kubernetes experience and 5 years of Python-based cloud infrastructure automation, systems integration, and technical problem-solving.
Nice to have
- 3+ years of GPU computing experience for ML/AI training and inference; hands-on experience with HPC/ML orchestration frameworks or deep learning frameworks.
- Understanding of cloud ML tools from NVIDIA, AWS, Azure, or Google.
Pay
$235k - $300k CAD (On Target Earnings)
Tools
Infrastructure as Code (IaC), Kubernetes, Python, Slurm, Kubeflow, TensorFlow, PyTorch, NVIDIA
AI focus
Supports AI/ML teams by designing cloud infrastructure and MLOps solutions, optimizing GPU-based training and inference pipelines, and advising customers on AI workloads.
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