Cloud Services Solutions Architect

at  NVIDIA

Join us at NVIDIA as a Cloud Services Solutions Architect and help our customers and partners adopt end-to-end AI solutions in the cloud! As a Solutions Architect, you’ll design, configure and deploy AI Training and Inference solutions in Public Clouds, as well as in Private Clouds based on groundbreaking NVIDIA technology. You’ll work with customers and partners to deploy and operationalize AI at scale by driving adoption for end-to-end Machine Learning and Deep Learning solutions in the cloud. If you are enthusiastic about projects that push the boundaries and mix latest Cloud technologies with revolutionary AI platforms, then read on!

What you’ll be doing:

• Build and deploy AI/ML solutions at scale using NVIDIA’s AI software on cloud-based GPU platforms
• Using your skills in AI, MLOps, ML engineering, DevOps, Kubernetes, and orchestration to deploy hybrid solutions
• Work as customer technical specialist to address customer workload, security & privacy and architectural requirements and seek their technical challenges
• Deliver customer on-boarding sessions and technical and architecture presentations with NVIDIA AI, Cloud and Networking technologies
• Run and own Proof of Concepts (PoCs), introducing NVIDIA Cloud Solutions and integrating them to new and existing accounts
• Debug SW issues, provide solutions to customers and report of bugs to NVIDIA’s product organization
• Work with NVIDIA’s product and architecture teams by providing customer requirements, feedback and prioritization

What we need to see:

• 8+ years of foundational expertise in Engineering, Computer Science, Data Science, or a related field
• Master’s Degree or Ph.D within Computer Science, Computer Engineering or similar field, or comparable work experience
• 3+ years of working experience in DevOps roles in the areas of Cloud Computing, Cluster Orchestration or AI Workloads
• Substantial experience in an IT role or alike for HPC or large scale AI systems
• In depth knowledge with orchestration platforms like Kubernetes, SLURM or OpenShift
• Expertise in Deep Learning and Machine Learning, with experience using deep learning frameworks such as TensorFlow or PyTorch
• Ideal candidate should understand how AI and HPC workloads interact with both HW and SW infrastructure
• Strong written and oral communication skills with the ability to optimally collaborate with customers, management and engineering
• Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects
• Strong analytical and problem-solving skills
• Good verbal communication and presentation skills in English

Ways to stand out from the crowd:

• Working experience with major or tier-2 cloud service providers (such as AWS, GCP and Azure), or with AI Datacenter Providers or HPC Datacenters
• Experience with AI frameworks and tools on GPUs
• Other European language skills than English
• Ability and wiliness to travel to end customers

NVIDIA is widely considered to be one of the technology world’s most desirable employers with very competitive benefits. We have some of the most forward-thinking and innovative people in the world working for us. If you’re creative and autonomous, we want to hear from you!

• Build and deploy AI/ML solutions at scale using NVIDIA’s AI software on cloud-based GPU platforms
• Using your skills in AI, MLOps, ML engineering, DevOps, Kubernetes, and orchestration to deploy hybrid solutions
• Work as customer technical specialist to address customer workload, security & privacy and architectural requirements and seek their technical challenges
• Deliver customer on-boarding sessions and technical and architecture presentations with NVIDIA AI, Cloud and Networking technologies
• Run and own Proof of Concepts (PoCs), introducing NVIDIA Cloud Solutions and integrating them to new and existing accounts
• Debug SW issues, provide solutions to customers and report of bugs to NVIDIA’s product organization
• Work with NVIDIA’s product and architecture teams by providing customer requirements, feedback and prioritizatio