Curated roles
Browse roles focused on reducing risks from advanced AI systems, including alignment research, safety engineering, evaluations and related operations.
364 active roles found.
Research engineer building evaluation and security testing systems for frontier AI models, including capability assessment, evasion testing, and risk mitigation.
Senior ML research role focused on developing models, experiments, and evaluation frameworks for AI safety problems, with explicit alignment and frontier-model safety relevance.
The role involves developing and evaluating probabilistic inference methods to support safe-by-design AI systems.
PhD research role focused on AI safety, evaluating large language models and frontier agentic systems to detect deceptive behavior and understand novel behaviors for safer AI development.
Senior research role focused on AI safety research, frontier-model red teaming, and evaluations in high-risk domains.
Leads Faculty's AI safety research team, overseeing research on safe language models and safety-critical systems, including evaluations and red-teaming in high-risk domains.
Senior developer role building an open-source security evaluation platform for AI agents, including scoring, auditable evaluation schemas, policy enforcement infrastructure, and threat modeling.
Full-stack software engineer building evaluation tooling and monitoring infrastructure for frontier AGI safety research, with direct support for scheming detection and mitigation work.
Backend software engineer on Apollo Research’s research team building evaluation tooling, LLM monitoring/control infrastructure, and other internal systems supporting frontier AGI safety research.
The role involves designing methods to ensure AI models align with goals, developing monitoring techniques, researching control mechanisms, and conducting red-team simulations.
Research scientist role focused on frontier AI risk evaluations, including designing evaluation harnesses and datasets, testing dangerous capabilities, and communicating results to policymakers.
The role involves running evaluations on frontier AI systems to assess risks, including pre-deployment evaluations and analyzing model behavior.
Research scientist/engineer role focused on studying scheming, misaligned preferences, and evaluation techniques for frontier AI systems.
The role involves developing methods to mitigate false information in large language models, creating evaluation protocols, and conducting research in LLM security and interpretability.
Role focused on AI behavioral evaluations and oversight for harmful model behaviors, policy requirements, and frontier lab evaluation work.
PhD fellowship focused on researching mechanistic interpretability methods to enhance the security of large language models and address misinformation.
AI Engineer building an adversarial AI evaluation platform for model performance, robustness, and risk evaluation, which is adjacent to AI safety work.
The Anthology Fund focuses on investments in trust and safety tooling that enhances AI safety and supports responsible AI deployment.
Full-stack engineering role building web applications and features for formal verification tools and AI safety infrastructure.
Technical staff role conducting AI alignment research, including threat modeling, empirical countermeasure testing, and communicating safety-focused findings.