Solutions Architect, Scientific GPU Compute

Responsibilities

• Serve as a technical and strategic advisor to Schmidt leadership and principal investigators across diverse scientific disciplines.
• Conduct deep-dive technical consultations to translate scientific goals into specific GPU, AI/ML, HPC, and cloud requirements.
• Lead the end-to-end onboarding of research teams onto Schmidt Sciences compute infrastructure.
• Act as a "Proposal Concierge" to help grantees align research proposals with available compute resources.
• Provide critical field insights from researchers to internal product and engineering teams to drive service improvements.

Requirements

• Post-graduate degree in a technical field such as computer science, biology, climate, or astrophysics.
• 8+ years of experience in AI/ML infrastructure and technical advisory.
• Hands-on expertise with cluster workload management using Slurm and Kubernetes.
• Understanding of the tech stack required to design, train, deploy, and maintain state-of-the-art AI models at production scale.
• Proficiency in technical writing for both expert and general audiences.
• Ability to travel within the U.S. on a regular basis.

Preferred Qualifications

• PhD in a relevant computational science or technical field.
• Proven track record of supporting large-scale scientific grant proposals.
• In-depth knowledge of data center storage and networking technologies.
• Proficiency with modern machine-learning hosting frameworks such as NVIDIA Dynamo, TensorFlow Serving, or Ray.
• Experience working with philanthropic organizations or academic/government research institutions.

About the Company

Schmidt Sciences is a nonprofit organization founded by Eric and Wendy Schmidt to accelerate scientific knowledge and breakthroughs. Through its AI Center, the organization supports research in areas including AI for science, the science of AI, and beneficial AI, providing the advanced tools and infrastructure necessary to support a thriving planet.