The role involves operationalizing risk management frameworks for frontier AI companies, focusing on safety evaluations, mitigation measures, and conducting red-teaming assessments.
Added todayParis, France, London, UKAI Compliance & Risk Management
504 active roles found
The role involves operationalizing risk management frameworks for frontier AI companies, focusing on safety evaluations, mitigation measures, and conducting red-teaming assessments.
The Research Scientist role involves solving research problems related to AI evaluation, robustness, and red teaming of language models.
This role invites individuals to engage in research on AI model threats, participate in evaluations, and influence AI policy initiatives.
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Internship focused on developing a reliability platform for LLM applications, including safety testing and verification of AI models.
The role focuses on building a platform for training and evaluating interpretable AI systems, emphasizing safety and reliability.
The role involves conducting research on AI security, focusing on protecting models against cyber threats and evaluating AI's cybersecurity capabilities.
The Research Engineer role involves building systems to evaluate and secure frontier AI models, focusing on risk mitigation and security testing.
The Technical Policy Researcher will address AI security issues, conduct threat modeling, develop taxonomies for AI capabilities, and create policy proposals.
The role involves designing and implementing ML models to address advanced AI safety challenges, collaborating with researchers, and developing evaluation frameworks.
The role involves developing and evaluating probabilistic inference methods to support safe-by-design AI systems.
Lead RAND's AI cyber evaluation agenda, focusing on assessing AI models' offensive cyber capabilities and developing benchmarks for performance.
PhD research position focused on AI safety, investigating large language models and evaluating AI systems to ensure safe development.
Lead AI safety research and conduct red teaming for frontier models in sensitive domains.
Lead Faculty's AI safety research team, focusing on safe AI systems and conducting research on large language models.
The Applied AI Engineer role focuses on developing ML methods for assessing biological threats and creating evaluation frameworks for model performance.
The role involves developing AI safety strategies, building evaluations for scientific risks, and creating safeguards against unsafe AI behavior.
The role involves designing and building production systems for evaluating and securing frontier AI models.
Lead AI safety strategy and evaluate risks related to scientific superintelligence in biological and physical sciences.
The role involves designing and implementing safety strategies for AI systems in biological and physical sciences, including risk evaluations and threat modeling.
The role involves designing and building a security evaluation platform for AI agents, focusing on threat models, evaluation schemas, and policy enforcement.