Solutions Architect, Scientific GPU Compute

About the AI & Advanced Computing Center (“AI Center”)

The AI Center is a grantmaking and research group that views AI as a transformative force for scientific discovery and societal progress. Over the next decade, we aim to support key researchers who are working to make AI systems competent, trustworthy, reliable, and able to effectively partner with human scientists on the next generation of discovery. We will also make distinctive investments in beneficial AI areas where philanthropy has a unique advantage. By supporting enabling infrastructure, foundational research, and targeted programs in science disciplines, the AI Center will create the conditions for AI-enabled discovery to achieve its promise.

The AI Center currently has three focus areas:

• AI for Science - using AI to improve how scientists generate hypotheses, conduct experiments, analyze data, and produce new knowledge - and do this in a way that specifically accelerates the discovery process.
• Science of AI - understanding and controlling AI systems to mitigate and manage potential risks from advanced AI. Improve AI reliability and performance in areas of limited commercial interest.
• Beneficial AI - providing scientific foundations and datasets for understanding the larger human impacts of AI.

These programs support and draw on related Schmidt Sciences engagements, such as the Virtual Institute for Scientific Software (VISS), which seeks to accelerate the pace of scientific discovery through the support and development of high-quality, community-oriented scientific software. These philanthropic efforts support experienced engineers who are tasked with building open-source infrastructure and applications for multi-disciplinary, high-performance, at-scale scientific discovery.

The Role

We are seeking a technical advisor to bridge the gap between cutting-edge scientific research and high-performance computing (HPC) infrastructure. In this role, you will serve as the primary strategic liaison for Schmidt Sciences-funded researchers globally, working across all scientific disciplines-including climate, synthetic biology, astrophysics, AI & advanced computing-to accelerate discovery through advanced compute resources. You will be responsible for evaluating the complex GPU and AI/ML needs of world-class researchers, and leading the technical onboarding process to ensure their initiatives are successfully deployed on a wide range of compute platforms. This role reports to the director of the AI Institute at Schmidt Sciences. Over time, this role may have direct reports.

Key Responsibilities:

• Grantee Strategic Advisory: Serve as a technical and strategic advisor to Schmidt leadership and principal investigators across a diverse portfolio of scientific disciplines.
• Compute Needs Assessment: Conduct deep-dive technical consultations with academic labs and other research organizations to translate scientific goals into specific GPU, AI/ML, and HPC and cloud requirements.
• Technical Onboarding & Enablement: Lead the end-to-end onboarding of research teams and grantee institutions onto the Schmidt Sciences compute infrastructure, and provide comprehensive training to boost cloud and compute proficiency of our users.
• Resource Advocacy: Act as a "Proposal Concierge," helping grantees align their research proposals and research activities with the available compute resources to maximize scientific impact.
• Feedback Loop: Deliver critical field insights from researchers to internal product and engineering teams to drive the continuous improvement of compute services and research tools.

Required Knowledge, Skills, and Abilities:

• Advanced Scientific Background: A post-graduate degree in a technical field such as computer science, biology, climate, astrophysics, or a related computational science
• Computing Expertise: 8+ years of combined experience spanning AI/ML infrastructure and research-facing technical advisory; experience building networks across academic, nonprofit, or government research is strongly preferred
• Cross-Disciplinary Communication: Exceptional ability to communicate complex technical and scientific concepts to both high-impact research scientists and executive leadership.
• Hands-on experience with cluster workload management using Slurm and Kubernetes.
• Successful track record of accelerating time from grant approval to first result for computationally intensive projects.
• History of collaborative impact in high-intensity, team-based environments.
• Sense of controlled urgency in driving work to completion.
• The highest integrity and ability to maintain confidentiality.
• Be able to travel within the U.S. on a regular basis as needed.
• Understanding of the tech stack needed to design, train, deploy, and maintain state-of-the-art AI models at a production scale.
• Experience producing technical writing for expert and general audiences.

Preferred Knowledge, Skills, and Abilities:

• PhD in a technical field such as computer science, biology, climate, astrophysics, or a related computational science
• Grant & Funding Acumen: Proven track record of supporting large-scale, federally funded, or private scientific grant proposals.
• In-depth knowledge of data center storage and networking technologies and solutions.
• Proficiency with modern machine-learning hosting software frameworks, such as NVIDIA Dynamo, TensorFlow Serving, Ray, etc.
• Prior leadership of data center infrastructure initiatives and projects, such as evaluating hardware scalability, securing data, or executing large-scale upgrades.
• Expertise in relevant technical focus areas, e.g., AI model performance monitoring or network and storage optimization, etc.
• Expert-level experience and industry credentials in the software and hardware frameworks that drive modern AI, and competence in at least one, and preferably multiple, fields of science impacted by modern AI.
• Ability to work with and effectively translate technical concepts across multiple scientific disciplines.
• Ability to critically evaluate scientific and technical publications and emerging methods in related disciplines.
• Experience working with science-focused institutions such as philanthropic organizations or academic/government research institutions.