Frontier AI Safety Evaluator & Policy Auditor

Obsidian; Lisboa; Presencial; EUR 55 000 - 90 000; Tempo integral

Resumo da oferta

Obsidian is seeking experienced AI Safety Practitioners to evaluate the safety, quality, and alignment of frontier AI models across complex, policy-sensitive topics. You will assess AI-generated responses and provide structured feedback to improve model behavior.

Join a collaborative team of researchers and safety engineers to develop evaluation rubrics, identify unsafe outputs, and drive improvements in real-world, high-impact domains.

Qualificações

• 5+ years of professional experience in AI Safety, Trust & Safety, journalism, public policy, scientific research, or a related field.
• Excellent written English, critical thinking, and analytical reasoning skills.
• Ability to consistently evaluate nuanced and policy-sensitive scenarios.

Responsabilidades

• Evaluate AI-generated responses for safety, factual accuracy, policy compliance, and overall quality.
• Review content involving misinformation, political persuasion, self-harm, violence, cyber, biosecurity, and other sensitive domains.
• Apply and refine evaluation rubrics for RLHF, SFT, and AI safety benchmarking.
• Identify unsafe outputs, hallucinations, reasoning failures, and policy violations.
• Provide structured feedback to improve model alignment and safety performance.
• Collaborate with AI researchers and safety teams on ongoing evaluation initiatives.

Conhecimentos

Excellent written English

Critical thinking

Analytical reasoning

Policy-sensitive evaluation

Formação académica

Bachelor's degree or higher in Journalism, Communications, Psychology, Sociology, Public Policy, Law, Biology, Chemistry, Computer Science, or related discipline

Descrição da oferta de emprego

Obsidian is seeking experienced AI Safety Practitioners to evaluate the safety, quality, and alignment of frontier AI models across complex, policy-sensitive topics. You will assess AI-generated responses and provide structured feedback to improve model behavior.

Join a collaborative team of researchers and safety engineers to develop evaluation rubrics, identify unsafe outputs, and drive improvements in real-world, high-impact domains.