Solutions Architect Scientific GPU Compute

You will advise researchers on GPU, AI and machine-learning, HPC, and cloud requirements. You will lead technical onboarding and training, align research proposals with available compute resources, and share researcher feedback to improve compute services and research tools.

Responsibilities

• Advise leadership and principal investigators across scientific disciplines
• Conduct technical consultations to translate scientific goals into GPU, AI and machine-learning, HPC, and cloud requirements
• Lead onboarding of research teams and institutions onto compute infrastructure
• Provide training to improve cloud and compute proficiency
• Help grantees align proposals and research activities with available compute resources
• Deliver researcher insights to product and engineering teams to improve compute services and research tools

Requirements

• Post-graduate degree in computer science, biology, climate, astrophysics, or a related computational science field
• 8 or more years of combined AI and machine-learning infrastructure and research-facing technical advisory experience
• Ability to communicate complex technical and scientific concepts to research scientists and executive leadership
• Hands-on experience with Slurm and Kubernetes cluster workload management
• Track record of accelerating time from grant approval to first result for computationally intensive projects
• Understanding of the technology stack for production-scale AI models
• Technical writing experience for expert and general audiences
• Ability to travel within the United States regularly