About FAR.Research We explore promising research directions in AI safety and scale up only those showing a high potential for impact. Once the core research problems are solved, we work to scale them to a minimum viable prototype, demonstrating their validity to AI companies and governments to drive adoption. We are aiming to rapidly grow our team in the following areas especially, at varying levels of seniority: Evals and Red-Teaming Conducting pre- and post-release adversarial evaluations of frontier models (e.g. Claude 4 Opus, ChatGPT Agent, GPT-5); developing novel attacks to support this work; and exploring new threat models (e.g. persuasion, tampering risks).Infrastructure Maintaining GPU compute infrastructure to support experiments with open-weight models and developing new tooling to allow our research teams to scale their fine-tuning and post-training workflows to frontier open-weight models. We are also seeking more senior candidates in the following research areas: Mitigating AI Deception Studying when lie detectors induce honesty or evasion, and developing model organisms for deception and sandbagging Adversarial Robustness Working to rigorously solve these security problems through building a science of security and robustness for AI, from demonstrating superhuman systems can be vulnerable, to scaling laws for robustness and jailbreaking constitutional classifiers Mechanistic Interpretability Finding issues with Sparse Autoencoders, probing deception using AmongUs, understanding learned planning in SokoBan and interpretable data attribution. FAR.AI is one of the largest independent AI safety research institutes, and is rapidly growing with the goal of diversifying and deepening our research portfolio. We would welcome the opportunity to add new research directions if you are a senior researcher with a strong vision and would like to pitch us on it.
