The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We’re in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally.
We’re here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action.
TeamDescription
The Societal Impacts team studies high-impact societal risks caused by frontier AI deployment. Our team’s mandate is to build a rigorous, world-class evidence base for the safe and responsible development of frontier AI by identifying risks, measuring impacts, and informing mitigation strategies.
Risk areas we study include frontier AI enabling criminal activity, undermining trust in information, harming psychological wellbeing, and facilitating malicious social engineering.
Our work is highly interdisciplinary, drawing on methods from computational social science, AI safety and security, cognitive and behavioural science, machine learning, and data science. Typical projects include running rigorous human–AI interaction studies, building evaluations for AI models and products, and developing datasets to monitor risk exposure and severity.
Role Description
Successful candidates will be strong researchers and engineers, who work with our research scientists to design, implement and run experiments that answer important questions about the effects AI will have on society. Illustrative projects might include:
Implementing a human-AI interaction study where multiple human and AI participants converse and play a game
Building a pipeline to scrape and analyse publicly available AI agent implementations
Designing and running model evaluations for various societal risks from AI model behaviour
This is a multidisciplinary team, and we look for people with a diversity of backgrounds.
Data engineering, including data collection, data cleaning, processing, and visualisation
ML engineering, including experience training/evaluating models using PyTorch or a similar library
Full-stack web development
Knowledge of machine learning sufficient to understand recent papers in the field
Strong verbal communication, experience working on a collaborative research team, and interpersonal skills
Demonstrable interest in and understanding of the societal impacts of AI
Desired Skills and Experience
Building and maintaining complex data products
Designing and implementing experiments in human-AI interaction
Training or evaluation of frontier AI models
Research related to societal impacts of AI systems
A specialisation in a relevant field of social or political science, economics, cognitive science, criminology, security studies, AI safety, or another relevant field.
What We Offer
Impact you couldn't have anywhere else
Incredibly talented, mission-driven and supportive colleagues.
Direct influence on how frontier AI is governed and deployed globally.
Work with the Prime Minister’s AI Advisor and leading AI companies.
Opportunity to shape the first & best-resourced public-interest research team focused on AI security.
Resources & access
Pre-release access to multiple frontier models and ample compute.
Extensive operational support so you can focus on research and ship quickly.
Work with experts across national security, policy, AI research and adjacent sciences.
Growth & autonomy
If you’re talented and driven, you’ll own important problems early.
5 days off and annual stipends for learning and development, and funding for conferences and external collaborations.
Freedom to pursue research bets without product pressure.
Opportunities to publish and collaborate externally.
Life & family*
Modern central London office (cafes, food court, gym), or where applicable, option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol.
Hybrid working, flexibility for occasional remote work abroad and stipends for work-from-home equipment.
At least 25 days’ annual leave, 8 public holidays, extra team-wide breaks and 3 days off for volunteering.
Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option for additional unpaid time).
On top of your salary, we contribute 28.97% of your base salary to your pension.
Discounts and benefits for cycling to work, donations and retail/gyms.
*These benefits apply to direct employees. Benefits may differ for individuals joining through other employment arrangements such as secondments.
Salary
Annual salary is benchmarked to role scope and relevant experience. Most offers land between £65,000 and £145,000 made up of a base salary plus a technical allowance (take-home salary = base + technical allowance). An additional 28.97% employer pension contribution is paid on the base salary.
This role sits outside of the DDaT pay framework given the scope of this role requires in depth technical expertise in frontier AI safety, robustness and advanced AI architectures.
Artificial Intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see our candidate guidance for more information on appropriate and inappropriate use.
Internal Fraud Database
The Internal Fraud function of the Fraud, Error, Debt and Grants Function at the Cabinet Office processes details of civil servants who have been dismissed for committing internal fraud, or who would have been dismissed had they not resigned. The Cabinet Office receives the details from participating government organisations of civil servants who have been dismissed, or who would have been dismissed had they not resigned, for internal fraud. In instances such as this, civil servants are then banned for 5 years from further employment in the civil service. The Cabinet Office then processes this data and discloses a limited dataset back to DLUHC as a participating government organisations. DLUHC then carry out the pre employment checks so as to detect instances where known fraudsters are attempting to reapply for roles in the civil service. In this way, the policy is ensured and the repetition of internal fraud is prevented. For more information please see - Internal Fraud Register.
Security
Successful candidates must undergo a crim
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