The role

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 from any DACH country (Germany, Austria, Switzerland).

Your responsibilities will include:

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.)

We expect you to have:

5+ years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
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, fluency in German or French preferred
Customer-centric mindset

It will be an added bonus if you have:

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)