[Hiring] Solutions Architect @Nebius

Role Description

We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines. You’re welcome to work remotely from Canada.

• 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.)

Qualifications

• 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.

Requirements

• 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).

Benefits

• 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.