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Threat Modeller, DeepMind

Google DeepMind112 open roles

Where
New York, NY, USA; London, UK
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Your applicationOpen nowThreat Modeller, DeepMindGoogle DeepMind · New York, NY, USA; London, UK
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The clock on this job

Early applications get read.

9.0% of postings close within 7 days. Measured by our own scanner across the market. Google DeepMind postings stay open a median of 13 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.9%3 days
  3. 9.0%7 days
  4. 15.5%14 days
  5. 33.9%30 days
This job: first seen 33 hours ago

Google DeepMind median: 13 days open

The posting

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; London, UK.

Minimum qualifications:

  • PhD in Science, Engineering, Data Science or equivalent practical experience.
  • 3 years of experience designing qualitative and quantitative models.
  • 1 year of experience working within a national laboratory, research organization, government defense organization, military intelligence unit, or specialized research organization.

Preferred qualifications:

  • Experience executing independent projects and synthesizing large datasets under tight deadlines in fast-paced environments.
  • Experience red-teaming, evaluating, utilizing LLMs to identify systematic vulnerabilities and potential misuse.
  • Experience communicating complex, high-consequence technical CBRNe risks into clear, actionable insights for business leaders, corporate governance bodies, and policy experts
  • Strong knowledge of dual-risk components of CBRNE domains and laboratory/defense paradigms.
  • Understanding of model evaluation methodologies for determining the frontier risks of modern AI models; see Google's FSF and similar documents at other AI labs.
  • Proven track record reviewing complex technical reports and identifying critical risks and vulnerabilities under tight timeframes.

About the job

Google’s CBRNE team (Chemical, Biological, Radiological, Nuclear and Explosives) makes sure that as Gemini gets better at science, it does not become a tool for catastrophic harm. We would like to invite applications for the position of a Threat Modeller Subject Matter Expert (SME) in the CBRNE team.

In this role, you will work intently with the Threat Modeling Lead to serve as a critical operational linchpin responsible for building out, maturing, and maintaining the threat models that evaluate and support the mitigation of dual-use risks of Google DeepMind’s most advanced AI models. Your work will contribute directly into the frontier safety framework (FSF), providing the rigorous risk-calibration needed to inform model releases and ensure safety-critical deployments.

We need a "doer", someone with the operational discipline to absorb vast quantities of complex scientific data, identify critical blind spots, and execute swiftly in a fast-paced environment. You will have an opportunity to apply real-world threat intelligence to the vanguard of artificial intelligence safety.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Refine and maintain the threat modeling framework to define critical thresholds, and integrate models into FSF review processes to support deployment decision-making.
  • Partner cross-functionally to design and implement evaluations identifying CBRNe-related risks in high-capability AI models.
  • Collaborate across evaluation and mitigation teams to determine if deployment safeguards are adequate for high-capability models.
  • Engage with external stakeholders, including governmental entities, third-party organisations (including the Frontier Model Forum) and subject matter experts.
  • Monitor the external competitor landscape, emerging dual-use methodologies and broader frontier AI domain.
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