About the Company

At Faculty, we transform organisational performance through safe, impactful, and human-centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award-winning Fellowship programme. Our expert team brings together leaders from across government, academia, and global tech giants to solve the biggest challenges in applied AI.

Faculty conducts critical red teaming and builds evaluations for misuse capabilities in sensitive areas, such as CBRN, cybersecurity, and international security, for several leading frontier model developers and national safety institutes. Notably, our work has been featured in OpenAI's system card for o1. Our commitment also extends to conducting fundamental technical research on mitigation strategies, with our findings published in peer-reviewed conferences and delivered to national security institutes. We design evaluations for model developers across broader safety-relevant fields, including the societal impacts of increasingly capable frontier models, showcasing our expertise across the safety landscape.

About the Role

Job Title: Lead Research Scientist
Location: London - Hybrid
Employment Type: Full-time
Department: Research & Development

As a Lead Research Scientist at Faculty, you will lead 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.

What You’ll Be Doing

Your role will evolve alongside business needs, but you can expect your key responsibilities to include:

Who We Are Looking For

• A proven track record of high-impact AI research, evidenced by top-tier academic publications (ideally in top machine learning or NLP conferences like 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, focusing on areas such as robustness, explainability, or uncertainty estimation.
• Advanced programming and mathematical skills with Python and experience with the standard Python data science stack (NumPy, pandas, Scikit-learn, etc.).

Bonus Qualifications

The following would be a bonus, but are by no means required:

• Commercial experience applying AI safety principles in practical or high-stakes contexts.
• Background in red-teaming, evaluations, or safety testing for government or industry applications.
• Academic research experience in a STEM or related subject. A PhD is great, but certainly not necessary.

What We Can Offer You

The Faculty team is diverse and distinctive, coming from different personal, professional, and organisational backgrounds. We all share a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals, and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.