Curated roles
Browse roles focused on reducing risks from advanced AI systems, including alignment research, safety engineering, evaluations and related operations.
357 active roles found.
Lead role at DeepMind focused on threat modeling and safety evaluations for CBRNe risks in advanced AI models, supporting the Frontier Safety Framework and deployment decisions.
Funding call for foundational research on safety and risk in multi-agent AI systems, including emergent dynamics, trustworthy interaction infrastructure, and scalable monitoring and control.
An 8-week in-person residency for engineers and researchers working on frontier AI security and verification, including projects to mitigate frontier AI risks and secure AI systems and infrastructure.
Research engineer role focused on building and maintaining AI safety evaluation benchmarks, guardrails, and research on agentic failure modes.
Three AI research engineer roles building the safety-pretraining stack for Apertus, including evaluation/red-teaming, synthetic data, and training systems for open frontier LLMs.
Research engineer role at DeepMind focused on frontier AI safety risk assessment, including measuring and mitigating advanced model risks, loss of control, and harmful manipulation.
Technical program management role leading frontier safety operations, safety frameworks, evaluations, and mitigation processes for Google DeepMind’s frontier AI development.
Research engineer role on DeepMind's Frontier Safety Mitigation team building evaluations, red-teaming, monitoring, and mitigations to reduce misuse and dangerous capabilities in frontier AI models.
Research role on Microsoft’s Futures Team focused on frontier risk and alignment, including frontier safety, normative model behaviour, alignment frameworks, evaluations, and mitigation pathways.
Senior ML engineer role building product experiences, evaluation systems, and trustworthy language-model workflows for research and high-stakes decision-making; relevant because it explicitly emphasizes careful evaluations, process supervision, and safer AI systems.
Senior virology and biosecurity role at Google DeepMind focused on biosecurity mitigation, biology evaluations, and protecting frontier AI models from biological misuse.
Senior security engineer role on DeepMind's Agentic Red Team focused on adversarial testing of AI agents, prompt injection, exploit development, and automated red-teaming frameworks for model safety.
Research positions in NLP and AI with a strong emphasis on trustworthy and safe AI, including agent reliability, evaluation science, interpretability, red-teaming, and robustness.
Remote researcher role producing public reviews of AI benchmarks, evaluating methodologies and implications for AI capabilities; adjacent to AI safety via model evaluations and capability assessment.
Senior research management role supporting AI safety programmes, including scoping and reviewing research, mentoring researchers, and running red-teaming and proposal development sessions focused on reducing AI risk.
Research scientist role at a non-profit AI safety lab focused on theoretical and empirical work on LLM-based agents, loss-of-control risks, and safety mitigations.
Senior technical role building and securing frontier AI datacenter infrastructure, including threat modeling and red-teaming against nation-state adversaries.
Senior technical role on Cohere’s Safety for Agents team focused on data generation, post-training algorithms, and evaluation methods to improve safety, trustworthiness, and security of LLMs and agentic models.
Research scientist role at Resolution focused on technical AI alignment research, including empirical and theoretical work on scalable oversight and related alignment problems.
Research Engineer role at an ASI alignment lab, building research automation and evaluation infrastructure to support alignment research and frontier-model experiments.