28 days ago
Remote, CanadaSenior / Staff+
Responsibilities
- Advise customers throughout engagements and provide technical guidance on GPU cloud technologies and best practices.
- Conduct proofs of concept, workshops, presentations, and training sessions.
- Understand customer requirements and design aligned solution architectures.
- Design and document infrastructure-as-code solutions, technical documentation, and how-to guides.
- Optimize customer pipeline performance, scalability, and cloud resource utilization.
- Serve as the internal subject-matter expert for customer scenarios across product, technical support, and marketing teams.
- Support marketing events including hackathons, conferences, workshops, and webinars.
Requirements
- 5–10+ years of experience as a cloud solutions architect, systems or network engineer, developer, or similar technical professional focused on cloud computing.
- Bachelor’s degree or foreign equivalent in a related field, or an equivalent combination of education and relevant experience.
- Hands-on experience with infrastructure-as-code and configuration-management tools, preferably Terraform and Ansible.
- Experience with Kubernetes and Python programming.
- Understanding of GPU computing for ML training and inference, including GPU drivers, libraries, CUDA, and OpenCL.
- Strong communication skills and a customer-centric mindset.
- Experience with HPC or ML orchestration frameworks such as Slurm or Kubeflow is a preferred qualification.
- Experience with deep learning frameworks such as TensorFlow or PyTorch is preferred.
- Understanding of cloud ML tools from NVIDIA, AWS, Azure, or Google is preferred.
Benefits
- Competitive compensation and benefits packages.
- Career growth and learning opportunities.
- Flexibility and ownership.
- Collaborative and innovative culture.
- Opportunity to work on impactful AI projects.
- International environment and talented teams.
- Remote work from Canada.
About Nebius
Nebius builds a full-stack AI cloud offering GPU compute, storage, and tools for training and deploying ML models for startups, enterprises, and research labs. It sells consumption-based cloud infrastructure (IaaS/PaaS) and managed services tailored to generative AI workloads, including large-scale model training and inference. The company is headquartered in Amsterdam and operates as an independent provider.