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About the Role
Conduct original technical research in AI safety to build the foundation for safe, trustworthy AI deployment. Design and execute impactful experiments, study model behavior, and develop robust, reproducible tooling. Bridge scientific discovery with practical application, helping translate complex technical insights for external partners, frontier labs, and national security institutes.
Responsibilities
- Execute technical research in AI safety by designing and running experiments to study and steer model behavior.
- Apply white-box and black-box methodologies, focusing on interpretability, steering, and behavioral studies of transformer-based LLMs.
- Develop high-quality, modular, and reproducible research code in Python using deep learning frameworks like PyTorch.
- Build and maintain research infrastructure and technical tooling to accelerate scientific discovery.
- Document and communicate experimental findings through high-quality academic papers, technical reports, and presentations.
- Collaborate with senior scientists to identify literature gaps, refine hypotheses, and identify research scope.
- Translate complex technical insights for diverse audiences, including external frontier labs, government bodies, and safety institutes.
Requirements
- Solid background in machine learning fundamentals and transformer architectures (specifically LLMs).
- Practical understanding of white-box and black-box interpretability techniques, such as steering vectors or mechanistic interpretability.
- Demonstrated capability to take structured technical problems and formulate hypotheses.
- Strong programming skills in Python and deep learning frameworks like PyTorch, with a track record of writing clean, modular research code, using Git for version control.
- Excellent communication, enabling translation of complex technical concepts and experimental results into clear reports and presentations.
- Curiosity and analytical rigour, combined with exposure to core AI safety areas such as robustness, evaluations, or uncertainty calibration.
Skills
- Python
- PyTorch
- Git
- Machine Learning
- Transformer Architectures
- LLMs
- Interpretability Techniques
- AI Safety
Location
- Hybrid Working
Work Type
- Hybrid Working
- Part-time hours
Experience Level
- Research Scientist
Benefits
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family-Friendly Flexibility & Flexible working
- Sanctus Coaching
About the Company
- Faculty was established in 2014 with the belief that AI would be the most important technology of our time.
- Faculty has worked with over 350 global customers to transform their performance through human-centric AI.
- Faculty innovates, builds, and deploys responsible AI that makes a significant impact.
- Faculty possesses unparalleled depth of technical, product, and delivery expertise.
- Faculty serves clients across government, finance, retail, energy, life sciences, and defense.
- Faculty is growing rapidly in business and reputation.
- Faculty seeks individuals with intellectual curiosity and a desire to build a positive legacy through technology.
- Faculty empowers employees to envision and implement the most powerful applications of AI.
Equal Opportunity
- Faculty aims to grow the best team, not the most similar one, recognizing that diversity of individuals fosters diversity of thought.
- Faculty believes diverse teams deliver better work, relevant to the world.
- Faculty is united by deep intellectual curiosity and a desire to use abilities for measurable positive impact.
- Faculty strongly encourages applications from people of all backgrounds, ethnicities, genders, religions, and sexual orientations.