Deepmind jobs in London

The UK AI Security Institute is the world's largest and best-funded team dedicated to understanding the capabilities and impacts of advanced AI and developing practical risk mitigations. We’re in the heart of the UK government with direct lines to No. 10, 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, agility and international influence, this is the best place to shape both AI development and government action to ensure AI systems are deployed safely and responsibly.

Risks from misaligned AI systems will grow in importance as AI systems become more capable, autonomous, and integrated into society. AI control measures seek to detect, constrain, and/or counteract potentially misaligned AI models; we expect these measures to become increasingly important in the face of capable AI systems that may be unreliable, deceptive, or misaligned.

The Control Red Team partners with leading frontier AI companies to stress-test control measures. The team uses techniques from adversarial ML to develop algorithms to find a range of failures in control measures, which are then used to assess strengthen control measures. These partnerships allow us to directly influence vital control measures, while our position in government lets us bring our understanding of the state of control measures to broader government as they make critical deployment, research, and policy decisions.

The Control Red Team grew out of our previous work on control, including a library for running AI control experiments, stress-testing asynchronous monitors, chain-of-thought monitorability, evaluating control for LLM agents, practical challenges of control monitoring, and AI control safety cases. The Control Red Team additionally draws from expertise within our broader Red Team, which has world-leading expertise in human-led attacks against AI systems.

We're looking for an experienced researcher to lead the Control sub-team, driving its research agenda and managing a team of talented research scientists. The ideal candidate combines deep technical expertise in AI control and alignment with the leadership ability to set direction, develop people, and represent the team's work to senior stakeholders inside and outside government.

As Sub Team Lead, you will shape the Control sub-team's strategy and priorities with the Red Team lead, mentor junior and senior researchers, and serve as a key point of contact with frontier AI labs, UK government officials, and international partners. You'll work closely with the broader Red Team leadership – currently led by Xander Davies and advised by Yarin Gal – and collaborate with external teams including Redwood Research, Google DeepMind, Anthropic, and OpenAI.

Representative projects you might work on:

• Designing, building, running and evaluating methods to automatically attack and evaluate control protocols, such as LLM-automated attacking and optimisation approaches.
• Building and maintaining infrastructure and benchmarks for AI control experiments, including tools for evaluating the robustness of control measures across diverse threat models.
• Performing adversarial testing of frontier AI system control protocols and produce reports that are impactful and action-guiding for deployers.

In accordance with the Civil Service Commission rules, the following list contains all selection criteria for the interview process.

The experiences listed below should be interpreted as examples of the expertise we're looking for, as opposed to a list of everything we expect to find in one applicant:

You will be a good fit if you have:

• Hands-on research experience with large language models (LLMs) - such as training, fine-tuning, evaluation, or safety research.
• Experience working on AI alignment or AI control
• An ability to bring your own research ideas and work in a self-directed way, while also collaborating effectively and prioritising team efforts over extensive solo work.
• A demonstrated track record of peer-reviewed publications in top-tier ML conferences or journals.
• Ability and experience writing clean, documented research code for machine learning experiments, including experience with ML frameworks like PyTorch or evaluation frameworks like Inspect.
• A sense of mission, urgency, responsibility for success.

Strong candidates will also have:

• Experience working on adversarial robustness, other areas of AI security, or red teaming against any kind of system.
• Extensive experience writing production quality code.
• Desire to and experience with improving our team through mentoring and feedback.
• Experience designing, shipping, and maintaining complex technical products.
  

The Department for Science, Innovation and Technology offers a competitive mix of benefits including:

• A culture of flexible working, such as job sharing, homeworking and compressed hours.
• Automatic enrolment into the Civil Service Pension Scheme, with an employer contribution of 28.97%.
• A minimum of 25 days of paid annual leave, increasing by 1 day per year up to a maximum of 30.
• An extensive range of learning & professional development opportunities, which all staff are actively encouraged to pursue.
• Access to a range of retail, travel and lifestyle employee discounts.

Office attendance

The Department operates a discretionary hybrid working policy, which provides for a combination of working hours from your place of work and from your home in the UK. The current expectation for staff is to attend the office or non-home based location for 40-60% of the time over the accounting period.

Job contact :

• Name : Sarah Costello
• Email : Sarah.Costello@dsit.gov.uk

Recruitment team

• Email : Ben.Sams@dsit.gov.uk