Research Scientist, Multi-Agent Systems and Game Theory (Post-AGI Futures)

On-site in London·Added yesterday (last checked 7 Nov)

Google

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Our summary

Work mode: On-site, London
Experience: 2+ years

Skills

AI Safety

Requirements

What we're looking for

PhD in Computer Science, Machine Learning, Cognitive Science, Neuroscience, Economics, Sociology, Anthropology, Philosophy or a related technical field.
2 years of experience publishing research in core machine learning venues (e.g., NeurIPS, ICML, ICLR, JMLR, TMLR, etc.).

Nice to have

Experience constructing and evaluating multi-agent systems, environments, or behavioral research sandboxes.
Experience with interdisciplinary research on topics that fall outside of those covered by the core machine learning venues (e.g., cognitive science, tech policy and governance, social sciences, etc.).
Experience writing perspective/review style articles on technical topics.
Deep understanding and interest in artificial general intelligence and its potential for broader societal impacts.
Familiarity with institutional analysis frameworks and collective action models.

The role

Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

What you'll do

Drive research on mapping post-AGI societal dynamics using interdisciplinary computational and theoretical methods.
Collaborate with social scientists, philosophers, and machine learning researchers to study the impact of AGI on society.
Design, formalize, simulate, and evaluate multi-agent environments to model societies and large-scale agent collectives.
Stay current with the latest research literature and advancements across multi-agent AI research, LLMs, game theory, AI safety/ethics/governance, and other relevant social science or philosophy topics.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all

Apply online
Assessments
Online test · Not every role
You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.
Recruiter conversations
With a recruiter · Phone call · 1–2 sessions
One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.
Project work
In your own time · Not every role
For some roles, a small project before interviews: a case study, writing or code samples.
Interviews
With a rotating cast of Googlers
A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.
Decision and offer · With a recruiter

Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
AI tools are not permitted during interviews.
For some roles, pre-selected interviews happen virtually before final interviews onsite.