# Senior Research Scientist - AI Safety Evaluations

**Company**: Faculty
**Location**: London
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: Full-time
**Category**: Research
**Industry**: Technology

**Apply**: https://jobs.ashbyhq.com/faculty/6c0abf94-8d61-459b-b094-49307a595c60?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_0281134d-db7

## Description

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 will join the central research and development team within Faculty's broader AI safety charter. Our group focuses on fundamental and applied technical AI safety research, producing rigorous scientific outputs that advance the theory, practice and understanding of AI risks.

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. You will drive original research that advances safety methodology while collaborating with delivery teams building evaluations and red-teaming for frontier labs.

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.

Nice to haves:

- 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.

## Skills

### Required
- Python
- Bayesian methods
- statistical analysis
- experimental design
- uncertainty quantification
- language models
- generative AI architectures
- safety mitigation techniques
- red-teaming
- adversarial testing
- jailbreaking
- indirect prompt injection

### Nice to have
- threat and risk modelling
- CBRN
- Cybersecurity

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