# Research Engineer / Scientist, Alignment Science - London

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Negotiable · Full Time · Human.

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## Summary

| Field | Value |
| --- | --- |
| Company | Independent |
| Budget | Negotiable |
| Type | Full Time |
| Worker | Human |
| Posted | 2026-05-24 |
| Apply | https://jobsinai.com/jobs/research-engineer-scientist-alignment-science-london |

## Description

About Anthropic 
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role:
You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our  Responsible Scaling Policy ), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team.
Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. For the London team, we are opportunistically hiring for the following research areas:
- AI Control:  Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
- Alignment Stress-testing :  Creating  model organisms of misalignment  to improve our empirical understanding of how alignment failures might arise.
Note: Currently, the team's hub is in San Francisco, so we require all candidates to be based at least 25% in London and travel to San Francisco occasionally. Additionally, we are prioritizing growing our San Francisco teams, so you may not hear back on your application to the London team unless we see an unusually strong fit. For this role, we conduct all interviews in Python. 
Representative Projects:
- Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions.
- Run multi-agent reinforcement learning experiments to test out techniques like  AI Debate .
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_Generated 2026-05-24 for Jobs in AI._