Senior Research Scientist - AI Safety Evaluations
FacultyDecision Intelligence company
London, United KingdomSenior
LocalGlobe
Apax Digital
Metaplanet Holdings
Mercuri
Moonfire
Guardian Media Group Ventures
Data & AI
About the role
TL;DR
Lead AI safety evaluations to quantify risks in critical domains.
- •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.
- •Key Responsibilities Leading the development of novel safety evaluations in high-impact domains such as CBRN and Cyber to quantify emerging risks.
- •Executing original technical research in AI safety evaluation methods, taking ideas from concept to publication.
- •Shaping the R&D agenda by identifying strategic opportunities to advance safety evaluation methodology across Faculty and the broader ecosystem.
- •Contributing thought leadership and deep technical expertise to client delivery projects, evaluation work, and red-teaming for frontier labs.
- •Representing Faculty's scientific leadership through active external engagement with the global research community, frontier labs, and government stakeholders.
- •Requirements A track record of owning research end-to-end—from identifying novel problems to publication—driven by scientific curiosity and tenacity.
- •Hands-on experience designing and building AI evaluations or benchmarks, alongside a strong ability to reason about construct validity and mitigate confounds.
- •Expertise in red-teaming, adversarial testing, jailbreaking, indirect prompt injection, and assessing the robustness of model safeguards.
- •Strong foundational skills in experimental design, statistical analysis, and uncertainty quantification, including Bayesian methods.
- •Deep knowledge of language models, generative AI architectures, training methodologies, and safety mitigation techniques.
- •Solid Python proficiency combined with the engineering discipline required to build robust, reproducible research.
Required skills
PythonTensorFlowscikit-learnHugging FaceNLPMLflowKubeflowAnthropic APIPandasNumPy
Domain expertise
ai
Benefits & perks
Unlimited Annual Leave Policy, Private healthcare and dental, Enhanced parental leave, Family-Friendly Flexibility & Flexible working, Sanctus Coaching, Hybrid Working
Tech stack
PythonTensorFlowscikit-learnHugging FaceNLPMLflowKubeflowAnthropic APIPandasNumPy