Senior Research Scientist - AI Safety Evaluations
HybridLondon, England, United Kingdom
Job Summary
Lead the development of novel safety evaluations in high-impact domains like CBRN and Cyber to quantify emerging risks. Execute original technical research in AI safety evaluation methods, taking ideas from concept to publication. Shape the R&D agenda by identifying strategic opportunities to advance safety evaluation methodology across Faculty and the broader ecosystem. Contribute thought leadership and deep technical expertise to client delivery projects, evaluation work, and red-teaming for frontier labs. Represent Faculty's scientific leadership through active external engagement with the global research community, frontier labs, and government stakeholders.
Required Qualifications
- 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.
Desired Qualifications
- Experience in threat and risk modelling.
- Background or knowledge in high-risk domains such as CBRN or Cybersecurity.
- A history of high-impact AI research, evidenced by top-tier publications or equivalent practical achievements.
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