Google DeepMind
Biologist, DeepMind
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Minimum qualifications:
- PhD in Wet-Lab Virology, Microbiology, Biology, or a related field, or equivalent practical experience.
- 3 years of wet-lab experience with dual-use research, high-consequence pathogens, or biological toxins.
- Experience utilizing LLMs or narrow-use AI models to analyze and mitigate biological risks.
- Authored peer-reviewed publications across microbiology, virology, host-pathogen interactions, protein biochemistry, or immunology.
Preferred qualifications:
- Experience working in AI safety, evaluations, red-teaming, or applied AI research at a national laboratory, academic institution, or industry setting.
- Experience in using command line tools or coding.
- Proven application of biosecurity and biosafety concepts, including identifying misuse scenarios of emerging technologies.
- Knowledge of challenges of biological weapons, the biological threat landscape, potential mitigations and awareness of relevant stakeholders.
- Knowledge of the intersection of microbiology/virology within AI safety and Safety Frameworks in AI.
- Active security clearance, or the eligibility to obtain and maintain one.
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 from qualified biologists/microbiologists for the position of a biologist/microbiologist Subject Matter Expert (SME) in the CBRNE team within the Responsible Frontier AI Research (RFAIR) team, joining SMEs with broad experience across biology.
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You will work as a Research Scientist, serving as a technical expert responsible for evaluating and mitigating safety risks of frontier AI models (primarily but not limited to LLMs) in the biology domain; specifically, model assistance in the acquisition, development and dissemination of harmful biological agents and other dual use entities.
Artificial intelligence will be one of humanity’s most transformative inventions. At 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 learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Responsibilities
- Be responsible to test, evaluate, and mitigate harmful capabilities of frontier AI models in the biology domain.
- Design, develop and execute biology evaluations, assessments, frameworks, and red-teaming strategies to test the capability, safety, and uplift of AI models and support the development of mitigations.
- Collaborate with CBRNE/Responsibility engineers to ensure blocks on harmful outputs without overly degrading the model's scientific utility, requiring a deep understanding of dual use science.
- Partner with experts in various fields of CBRN, science, AI ethics, policy and safety.
- Support the ongoing development and refinement of Google’s CBRNE safety policy, and clearly communicating complex risks, evaluation findings, and mitigation strategies to leadership and technical and non-technical external stakeholders.
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Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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