Why Faculty?

We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.

We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.

Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.

AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.

About the Team

We are the central research and development team driving Faculty's broader AI safety charter. We pioneer fundamental and applied technical AI safety research, producing rigorous scientific outputs—including publications, tooling, and technical reports—that advance the theory and practice of AI safety and directly shape the work of frontier AI labs, government agencies, and national security institutes.

Our research spans both black-box and white-box approaches to understanding and steering AI systems. We care deeply about interpretability, faithfulness, and principled mitigation strategies, with a particular focus on the mechanistic and behavioural study of transformer-based large language models and long-running agentic systems.

We operate at the cutting edge of the field, with current research threads including:

System Understanding: Interpretability, steering vectors, and the science of evaluations.
Control & Alignment: Goal drift, machine unlearning, and uncertainty calibration.
Societal Safeguards: Misinformation mitigation and robust deployment boundaries.

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, and international security. That work has been conducted for several leading frontier model developers and national safety institutes, and has been featured in OpenAI's o1 system card and Meta Muse Spark’s Safety & Preparedness Report.

About the role

As a Senior Research Scientist at Faculty, you will join our high-impact R&D team to lead original technical research that advances our understanding of safe AI systems. Operating with high agency, you will balance scientific rigour with practical relevance to shape the future of safe AI deployment. Working closely with our broader AI safety practice, your scientific outputs—ranging from peer-reviewed publications to technical tooling—will directly inform frontier labs and government institutes, driving our entrepreneurial ambition to build a safer technological future.

What you'll be doing:

Leading original technical research in AI safety, steering projects from initial research question to high-impact publication.
Shaping the research agenda by identifying high-impact projects that balance scientific rigour with real-world relevance.
Contributing thought leadership and deep technical expertise to support wider evaluation and red-teaming efforts.
Supporting our positioning as a global leader through active external engagement with frontier labs and government stakeholders.
Developing robust, reproducible research code and engineering infrastructure to accelerate our scientific discovery.
Collaborating with cross-functional safety teams to translate fundamental research into practical mitigation strategies.

Who we're looking for:

Strong track record in AI research, evidenced by publications or equivalent experience, alongside the ability to tackle open, unsolved problems.
Capability to own research end-to-end, moving independently from framing novel problems to generating high-quality research artifacts.
Passion for technical AI safety, whether developed in academia, industry labs, or evaluation roles.
Deep knowledge of language models and generative AI architectures, including white-box techniques beyond API-level access.
Strong foundation in machine learning fundamentals, particularly in robustness, explainability, or uncertainty estimation.
Proficiency with deep learning frameworks like PyTorch and the Python skills required to build robust research tooling.

Our Recruitment Ethos

We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.

If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.

A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.