We are the central research and development team within Faculty’s broader AI safety charter. Our group focuses on fundamental and applied technical AI safety research, producing rigorous scientific outputs - publications, tooling, technical reports & evaluations - that advance the theory, practice and understanding of AI risks, and directly inform the work of frontier AI labs, government agencies, and national security institutes.
Our research spans fundamental research using black-box and white-box approaches to understand and steer AI systems, to building and advancing safety evaluations which better understand and quantify risks in AI. We care deeply about mechanistic understanding and scientific rigour in measuring risks in AI systems. Current research threads include (but are not limited to) uncertainty calibration, goal drift, misinformation mitigation, steering vectors, robust safeguard measurement and the science of evaluations.
We collaborate closely with the Faculty’s wider AI safety team, a group with a well-established track record in capability evaluations and red-teaming for misuse risk across CBRN, cybersecurity, societal and psychosocial harms. That work has been conducted for several leading frontier model developers and national safety institutes, and has been featured in model cards and safety reports from Anthropic, GDM, Meta & OpenAI.
As a Senior Research Scientist at Faculty, you will lead the development of cutting-edge safety evaluations to quantify AI risks in critical domains like CBRN and Cyber. Joining our high-impact R&D team, you will drive original research that advances safety methodology while collaborating with delivery teams building evaluations and red-teaming for frontier labs. This is a high-agency opportunity to conduct technical AI safety research that produces scientific outputs shaping the future of safe real-world AI deployment.