Autonomous Systems We're focused on extreme risks from autonomous AI systems - those capable of interacting with the real world. To address this, we're advancing the state of the science in risk modeling, incorporating insights from other safety-critical and adversarial domains, while developing our own novel techniques. We're also empirically evaluating these risks - building out one of the world's largest agentic evaluation suites, as well as pushing forward the science of model evaluations, to better understand the risks and predict their materialisation.
Role Summary As a manager, you'll be heading up a multi-disciplinary team including scientists, engineers and domain experts on the risks that we are investigating. Your team is given huge amounts of autonomy to chase research directions & build evaluations that relate to your team's over-arching threat model. This includes coming up with ways of breaking down the space of risks, as well as designing & building ways to evaluate them. All of this is done within an extremely collaborative environment, where everyone does a bit of everything. Some of the areas we focus on include:
Research and Development (R&D). Investigating AI systems' potential to conduct research, particularly in sensitive areas. This includes studying AI capabilities in developing dual-use technologies, unconventional weapons, and accelerating AI and hardware (GPU) development. Self-replication. Researching the potential for AI systems to autonomously replicate themselves across networks and studying their ability to establish persistence. Human influence. Assessing AI models' capacity to manipulate, persuade, or coerce individuals and groups. This covers techniques for general human influence, key individual manipulation, social fabric alteration, and the accumulation of social and political power. Dangerous resource acquisition. Examining AI models' ability to navigate restricted or illegal domains for acquiring resources or services. This encompasses research into general acquisition of dual-use resources, circumvention of embargoes and acquisition of human assets. Deceptive alignment. Evaluating AI systems' potential to display deceptive behaviours. This includes research into AI's ability to misrepresent its capabilities, conceal its true objectives, and strategically behave in ways that may not align with its actual goals or knowledge. How you can contribute In this role, you will be managing a team of exceptional and highly motivated individuals (we have people from OpenAI, DeepMind, Anthropic, Meta and AWS within Autonomous Systems). You'll also be growing your team at the beginning – getting involved with sourcing specific people we want, often world-leading experts in their domain, and then helping run the full process and getting them excited about the role.
Within your team, you're expected to provide strong management, including building relationships with team members, as well as giving regular feedback and coaching. You'll receive mentorship and coaching both from the work-stream lead (Alan Cooney), as well as the broader group of research directors in AISI (people like Geoffrey Irving and Yarin Gal). In addition, we have a strong learning culture including paper-reading groups and Friday afternoons dedicated to deep learning.
Person Specification You may be a good fit if you have some of the following skills, experience and attitudes:
Experience managing strong research or engineering teams, with well thought-out views on management philosophy and style. Experience coaching team members & providing feedback. Strong understanding of large language models (e.g. GPT-4). This includes both a broad understanding of the literature, as well as hands-on experience with either research or research engineering. Strong written and verbal communication skills. A track record of helping teams achieve exceptional things. Experience working with world-class multi-disciplinary teams (e.g. in a top-3 lab). Experience working within a research team that has delivered multiple exceptional scientific breakthroughs, in deep learning (or a related field). Strong track record of academic excellence (e.g. multiple spotlight papers at top-tier conferences). Acting as a bar raiser for interviews. Salary & Benefits We are hiring individuals at all ranges of seniority and experience within the research unit, and this advert allows you to apply for any of the roles within this range. We will discuss and calibrate with you as part of the process. The full range of salaries available is as follows:
L4: £85,000 - £95,000 L5: £105,000 - £115,000 L6: £125,000 - £135,000 There are a range of pension options available which can be found through the Civil Service website.
Selection Process In accordance with the Civil Service Commission rules, the following list contains all selection criteria for the interview process.
Required Experience We select based on skills and experience regarding the following areas:
Coaching & Mentoring Feedback Building Relationships Strategy Management Styles Engineering Leadership Research Leadership Verbal Communication Written Communication AI Safety Knowledge Frontier AI Knowledge & Experience Model Evaluations Knowledge Teamwork Interpersonal skills Tackle challenging problems Learn through coaching Desired Experience We may additionally factor in experience with any of the areas that our work-streams specialise in:
Autonomous systems Cyber security Chemistry or Biology Safeguards Safety Cases Societal Impacts
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