About the company
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel.
Responsibilities
- Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
- Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
- Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
- Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
- Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)
Requirements
- 5 - 10 + years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing.
- Bachelor’s degree or foreign equivalent in a related field, or an equivalent combination of education and relevant experience.
- Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python.
- Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL).
- Excellent communication skills.
- Customer-centric mindset.
Preferred qualifications
- Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow).
- Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch).
- Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google).
Conditions
- On Target Earnings Range: $235k - $300k CAD.
- Competitive compensation.
- Career growth and learning opportunities.
- Flexibility and ownership.
- Collaborative and innovative culture.
- Opportunity to work on impactful AI projects.
- International environment and talented teams.