Google DeepMind is looking to solve the problem of ensuring the safety of AI systems, specifically in the area of Chemical, Biological, Radiological and Nuclear (CBRN) risk assessment and mitigation.
Requirements
- Proven ability to write clean, maintainable, and efficient Python.
- Knowledge of concepts in mathematics, statistics, and machine learning needed for understanding cutting-edge research in AI, CBRN-related modeling, and risk assessment.
- Experience in CBRN threat analysis, risk assessment, modeling, or mitigation strategies.
- Familiarity with relevant datasets, benchmarks, or evaluation methodologies for CBRN risks in AI.
- Experience developing or working with safety-critical systems.
- Experience with data analysis tools and libraries for large-scale evaluation.
- Knowledge of international and national regulations or guidelines related to CBRN materials or technologies.
Responsibilities
- Design and develop robust evaluations to test potential CBRN risks arising from cutting-edge AI models with strong capabilities in the physical sciences.
- Develop and maintain infrastructure for these evaluations.
- Run these evaluations prior to releases for new AI models.
- Resolve potential CBRN risks with state-of-the-art mitigations.
- Clearly communicate results to decision-makers.
- Collaborate with subject matter experts in CBRN, AI policy and ethics, model development, and scientific research.
- Develop and maintain an understanding of trends in AI development, CBRN threat landscapes, governance, and relevant sociotechnical research to inform the design of new evaluations.
Other
- Bachelor's degree in a technical subject (e.g., computer science, engineering, machine learning, mathematics, physics, statistics) or a relevant scientific field with strong computational experience.
- Ability to present and explain technical results clearly to non-experts and leadership stakeholders.
- Master's or PhD in a field relevant to CBRN risk assessment or AI safety, such as chemical, biological, or nuclear engineering.
- Skill and interest in working on projects with many stakeholders, including scientific experts, policy teams, and engineers.
- Background check performed by a third party acting on our behalf.
