05 set - Roma
Obsidian
ppWe are seeking experienced bAI Safety Practitioners /b to evaluate the safety, quality, and alignment of frontier AI models across complex, policy-sensitive, and ambiguous ("grey-area") topics. You will assess AI-generated responses, apply safety policies, and help improve model behavior through structured evaluations and feedback. /ph3Responsibilities /h3ullipEvaluate AI-generated responses for safety, factual accuracy, policy compliance, and overall quality. /p /lilipReview content involving misinformation, political persuasion, self-harm, violence, cyber, biosecurity, and other sensitive domains. /p /lilipApply and refine evaluation rubrics for RLHF, SFT, and AI safety benchmarking. /p /lilipIdentify unsafe outputs, hallucinations, reasoning failures, and policy violations. /p /lilipProvide structured feedback to improve model alignment and safety performance. /p /lilipCollaborate with AI researchers and safety teams on ongoing evaluation initiatives. /p /li /ulh3Required Qualifications /h3ullipBachelor's degree or higher in Journalism, Communications, Psychology, Sociology, Public Policy, Law, Biology, Chemistry,
Computer Science, or a related discipline. /p /lilip5+ years of professional experience in AI Safety, Trust Safety, journalism, public policy, scientific research, security, or a related field. /p /lilipExcellent written English, critical thinking, and analytical reasoning skills. /p /lilipAbility to consistently evaluate nuanced and policy-sensitive scenarios. /p /li /ulh3Preferred Qualifications /h3ullipExperience with AI Safety, RLHF, SFT, Trust Safety, or AI evaluation. /p /lilipFamiliarity with safety policies, content moderation, or evaluation rubric development. /p /lilipExperience reviewing complex, high-risk, or ambiguous content. /p /li /ulh3Why Join? /h3ullipShape the safety and behaviour of frontier AI models used by millions worldwide. /p /lilipWork on challenging, real-world safety evaluations across nuanced and high-impact domains. /p /lilipCollaborate with leading AI researchers, engineers, and safety teams. /p /li /ul /p #J-18808-Ljbffr
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