About the position
RAND's Meselson Center, part of the Global and Emerging Risks (GER) division, is seeking an accomplished technical leader to drive our ambitious frontier AI security research agenda. As Research Lead - Securing Frontier AI, you'll direct a comprehensive research portfolio focused on ensuring that the world's most important AI systems are appropriately secured and addressing critical challenges at the intersection of AI, information security, and national security. You will be responsible for managing significant research budgets and personnel, overseeing complex technical research and policy analysis projects, and leading multidisciplinary teams of policy researchers, engineers, and scientists. Your work will shape recommendations for the White House, regulatory agencies, the intelligence community, other national governments, and industry leaders. Your team will communicate findings to both technical and non-technical audiences through quick-turnaround policy briefs and detailed technical analyses. A recent example of one of our research products is the Securing AI Model Weights report, which explored protecting frontier AI model weights from theft and misuse. This position is structured as a focused two-year appointment to create the urgency needed to drive ambitious change in this rapidly evolving field. Every day of your tenure will count toward achieving ambitious projects in AI security. The appointment may be renewed for an additional year, with options for longer-term employment at RAND thereafter. RAND's reputation for excellence is built on our commitment to high-quality, rigorous analysis and objectivity. As a Research Lead - Securing Frontier AI, you'll have access to RAND's leading researchers, extensive government and industry connections, and world-class analytical resources.
Responsibilities
- Direct a comprehensive research portfolio focused on AI security.
- Manage significant research budgets and personnel.
- Oversee complex technical research and policy analysis projects.
- Lead multidisciplinary teams of policy researchers, engineers, and scientists.
- Shape recommendations for the White House, regulatory agencies, and industry leaders.
- Communicate findings to technical and non-technical audiences.
Requirements
- 6+ years of technical experience in security engineering, software engineering, firmware engineering, hardware engineering, or related fields.
- 6+ years of technical management experience, including leading cross-functional teams, managing project budgets, and mentoring team members.
- Demonstrated ability to successfully lead complex projects to completion.
- Proficiency in Python, Java, C/C++, or other popular programming languages.
- Ability to develop rigorous and comprehensive threat models and identify potential system vulnerabilities.
- Strong ability to communicate effectively in English, both verbally and in writing.
- Ability to reason about policy options given different technical considerations.
- Ability to work effectively in a collaborative, multidisciplinary environment.
- Fluency with MS Office suite.
Nice-to-haves
- Graduate of the Computer Network Operations Development Program (CNODP), Remote Interactive Operator Training (RIOT), Future Operator Readiness Growth and Enrichment (FORGE), or equivalent experience.
- Experience with red team operations or offensive cyber capabilities development.
- Understanding of advanced persistent threat (APT) tactics, techniques, and procedures (TTPs) and experience with defending against them.
- Ability to think creatively about offensive and/or defensive techniques and strategies, beyond compliance with existing regulations.
- Familiarity with U.S. cybersecurity agencies, authorities, and policy development processes.
- Experience working in or with government on cybersecurity policy.
- Experience with advising non-technical stakeholders on security topics.
- Familiarity with the AI/ML hardware stack (e.g. GPUs, TPUs, data center design).
- Familiarity with the AI/ML software stack (e.g. CUDA, PyTorch, TensorFlow, Ray).
- Experience working on AI research, ML model training, or model deployment.
- Experience with securing AI systems.
Benefits
- Health insurance coverage.
- Life and disability insurance.
- Savings plan.
- Paid time-off.
- Sabbatical pay.
