Senior Research Engineer

About the AI Safety Institute

Advances in AI over the last decade have been rapid and surprising, and societal impacts will grow and accelerate. The AI Safety Institute (AISI) is the first state-backed organisation focused on frontier AI safety for the public interest. Its mission is to minimise surprise to the UK and humanity from rapid and unexpected advances in AI, and will work towards this by developing the sociotechnical infrastructure needed to understand the risks of advanced AI and support its governance. We are dedicated to progressing many aspects of this: from investigating current and future societal harms, over a wide range of misuse risks in areas like cyber and bio, to concerns of losing control of the AI systems we are building. While we have a strong focus on AI system evaluations, we are also spending significant effort on foundational research in the above areas and beyond.

• We look for candidates who care deeply about the societal impacts and long-term implications of their work and want to ensure a better future for the world.
• Diverse Perspectives: We believe that a range of experiences and backgrounds is essential to our success. We welcome individuals from all walks of life to join us in our shared endeavour.
• Collaborative Spirit: We thrive on teamwork and open collaboration, valuing every contribution, big or small.
• Innovation and Impact: We are dedicated to making a real-world difference in the field of AI safety, and we encourage innovative thinking and bold ideas.

Core Requirements

• You should be able to spend at least 4 days per week on working with us.
• You should be able to join us for at least 6 months.
• You should be able work from our office in London (Whitehall) for parts of the week but we provide lots of flexibility for remote work.
• We are open to working with your organisation on a secondment basis if your employer is open to this.

The Role

Research Engineers build and maintain scientific software to enable high quality research. They are uniquely placed to bridge the world of software engineering and research and are typically involved in diverse projects.

As a Research Engineer you might be embedding with one (or more) of our research teams. Here you will be collaborating with research scientists and people running evaluations and user studies on the one hand, and with our Platform Engineering team on the other. You might also on-board, run and improve existing evaluations from the wider research community, as well as up-scaling new evaluation methods developed in-house.

The Platform Engineering team will be providing the foundational infrastructure for our research projects. You will build on top of our platform to create bespoke, load-bearing infrastructure and tools for individual research projects. You will be able to independently run and analyse your own experiments to diagnose problems and understand our research work and tech stack in detail.

You will spend your time working not just on infrastructure code but also in the planning and execution of research projects, such as a wide range of evaluations of cutting-edge Frontier AI models. This includes working on analysing and visualising the outcomes of complex evaluation or fine-tuning procedures and managing large data sets.

As a research engineer it is your responsibility to make the hard trade-offs between when code needs to be load-bearing enough to support multiple experiments and when it is better to write “good enough" code to quickly prove or disprove a hypothesis. In this you will work very closely with our Research Scientists who will often be the main users for the tools you build.

Requirements & Experience

This role may be a great fit if you:

• Have excellent knowledge of training, fine-tuning, scaffolding, prompting, deploying, and/or evaluating current cutting-edge machine learning systems such as LLMs and Diffusion Models.
• Have at least 4+ years' experience working in a similar role in industry, relevant open-source collectives, or academia.
• Have experience conducting your own research, but most importantly as part of a cross-functional team.
• Possess a strong curiosity in understanding AI systems and have the ability to develop data collection, analysis and visualization interfaces to do so.
• Have substantial experience in building software systems to meet research requirements and have led or been a significant contributor to relevant software projects, demonstrating cross-functional collaboration skills.
• Deeply care about the user experience of a diverse range of users, from machine learning researchers to domain experts, to wide and diverse groups of human evaluators.
• Work independently and in a self-directed way, thriving in a constantly changing environment and a steadily growing team, while figuring out the best way to solve a particular problem.
• Bring your own voice and experience but also an eagerness to support your colleagues, being ready to do whatever is necessary for team’s success.
• Take responsibility for problems from beginning to end, demonstrating problem-solving abilities and preparedness to acquire any missing knowledge necessary to get the job done.