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About the Role

The Alignment Red Team is a specialized subteam within AISI's wider Red Team focused on detecting and evaluating misalignment in frontier AI systems. We perform novel research to develop techniques for finding misalignment, and pre- and post-deployment evaluations of frontier AI systems to understand loss-of-control risks associated with models, such as deceptive alignment, research sabotage, and reward-seeking.

Responsibilities

Researching methods to automatically search for misalignment in frontier models, including misalignment related to loss-of-control risks such as research sabotage and reward-seeking.
Building and running alignment evaluations relevant for loss-of-control risks that current benchmarks don’t capture.
Running pre-deployment evaluations to test the alignment of AI systems, and analysing and reporting results to frontier AI companies and UK and allied governments.
Contributing to public-facing research publications and technical reports that advance the field's understanding of misalignment risks and alignment evaluation methodology.
Designing and building software and tooling, including open-source software, for better alignment evaluations, improving efficiency, realism, and usability.
Conducting threat modelling, analysis, and conceptual thinking to understand crucial model behaviours that could lead to loss of control.
Performing alignment incident investigations to understand after the fact what drove certain kinds of misaligned behaviour in frontier models.
Mentoring and advising external collaborators and researchers to do work relevant to the team’s goals and alignment testing more broadly.

Requirements

Ability to work autonomously on complex research projects involving substantial engineering.
Completed at least one significant research project in AI safety, security or alignment involving engineering, experiment design and analysis on frontier LLMs.
Strong software engineering and ML experience writing complex projects involving language models and ML, beyond just research code.
1+ years professional experience programming in Python for ML or SWE work.
Experience writing clean, documented research code for machine learning experiments, including experience with ML frameworks like PyTorch or evaluation frameworks like Inspect.
Proven ability in a team environment – flexible, adaptive to needs, and willing to contribute wherever necessary.
Impact-driven mindset, motivated by doing the most important work rather than what's superficially impressive.
High velocity and high-quality bar for outputs.
Ability to make high-quality decisions by identifying risks and testing assumptions, demonstrated through strong prioritisation of research projects using clear, systematic criteria such as potential impact, feasibility, and the relative novelty of the research area.
Familiarity with alignment literature, current methods for post-training and aligning LLMs, loss-of-control risks and threat models, and the current state of the field.
High-quality research papers (first author at top ML venues such as NeurIPS, ICLR or ICML), particularly in relevant areas (such as AI safety, alignment, control, adversarial ML or evaluations).
Professional experience working on alignment or evaluations, especially at frontier labs or other frontier 3rd party evaluators.
Strong open-source software projects, particularly related to LLMs.
Proficient usage of LLM coding tools and agents.
Successful candidates must undergo a criminal record check and get BPSS clearance.
Eligibility for counter-terrorist check (CTC) clearance is preferred.

Skills

Python
PyTorch
Inspect
LLM coding tools
LLM agents

Location

London
Birmingham
Cardiff
Darlington
Edinburgh
Salford
Bristol

Work Type

Hybrid working
Occasional remote work abroad

Experience Level

Junior
Senior
Staff
Principal

Salary/Compensations

£65,000–£145,000
Level 3: £65,000–£75,000
Level 4: £85,000–£95,000
Level 5: £105,000–£115,000
Level 6: £125,000–£135,000
Level 7: £145,000

Benefits

Pre-release access to multiple frontier models and ample compute.
Extensive operational support.
Work with experts across national security, policy, AI research and adjacent sciences.
Own important problems early.
5 days off and annual stipends for learning and development.
Funding for conferences and external collaborations.
Freedom to pursue research bets without product pressure.
Opportunities to publish and collaborate externally.
Modern central London office, or option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol.
Stipends for work-from-home equipment.
At least 25 days’ annual leave.
8 public holidays.
Extra team-wide breaks.
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).
28.97% employer pension contribution.
Discounts and benefits for cycling to work, donations and retail/gyms.

About the Company

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.
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.

Equal Opportunity

The Civil Service embraces diversity and promotes equal opportunities.
We run a Disability Confident Scheme (DCS) for candidates with disabilities who meet the minimum selection criteria.
The Civil Service also offers a Redeployment Interview Scheme to civil servants who are at risk of redundancy, and who meet the minimum requirements for the advertised vacancy.
The Civil Service is committed to attract, retain and invest in talent wherever it is found.
As part of the application process, we monitor statistics on D&I.
We may be able to offer roles to applicant from any nationality or background.