Lead Research Scientist, Faculty

• A proven track record of high-impact AI research, evidenced by top-tier academic publications (ideally in top machine learning or NLP conferences ACL/Neurips, ICML, ICLR, AAAI) or equivalent experience (e.g. within model providers labs)
• Deep domain knowledge in language models and AI safety, with the ability to contribute well-informed views about the differential value, and tractability, of different parts of the traditional AI Safety research agenda, or other areas of machine learning (e.g. explainability)
• Practical experience of machine learning, with a focus on areas such as robustness, explainability, or uncertainty estimation
• Advanced programming and mathematical skills with Python and an experience with the standard Python data science stack (NumPy, pandas, Scikit-learn etc.)
• The ability to conduct and oversee complex technical research projects
• A passion for leading and developing technical teams; adopting a caring attitude towards the personal and professional development of others
• Excellent verbal and written communication skills

Desirable

• As a Lead Research Scientist at Faculty, you will be leading scientific research, and other researchers, in the area of AI safety that progresses scientific understanding
• You will contribute to both external publications, and Faculty’s commercial ambition to build safe AI systems
• This is a great opportunity to join a small, high agency team of machine learning researchers and practitioners applying data science and machine learning to business problems in the real world
• Lead the AI safety team’s research agenda, setting priorities and ensuring alignment with Faculty’s long-term goals
• Conduct and oversee the development of cutting-edge AI safety research, with a focus on large language models and other safety-critical AI systems
• Publish high-impact research in leading conferences and journals (e.g., NeurIPS, ACL, ICML, ICLR, AAAI)
• Support Faculty’s positioning as a leader in AI safety through thought leadership and stakeholder engagement
• Shape our research agenda by identifying impactful research opportunities and balancing scientific and practical priorities
• Interface with the wider business to ensure alignment between the R&D team’s research efforts and the company's long term goals with a specific focus in the AI safety and commercial projects in the space
• Build and lead a growing team of researchers, fostering a collaborative and innovative culture across a wide-range of AI Safety-relevant research topics
• Provide mentorship and technical guidance to researchers across diverse AI safety topics
• Lead hands-on contributions to technical research
• Collaborate on delivery of evaluations and red-teaming projects in high-risk domains, such as CBRN and cybersecurity, with a focus on government and commercial partners