Frontier AI Safety Evaluator

Mercor; Roma; Remoto; EUR 60.000 - 90.000; Tempo pieno

Descrizione del lavoro

Mercor is seeking experienced AI Safety Practitioners to evaluate the safety, quality, and alignment of frontier AI models across policy-sensitive topics. You will assess AI-generated responses, apply safety policies, and help improve model behavior through structured evaluations and feedback.

Responsibilities include evaluating safety and accuracy, reviewing high-risk content, refining evaluation rubrics for RLHF and AI safety benchmarking, and collaborating with research teams to drive safer

Competenze

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

Mansioni

• 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.

Conoscenze

Excellent written English

Critical thinking

Analytical reasoning

Formazione

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

Descrizione del lavoro

Mercor is seeking experienced AI Safety Practitioners to evaluate the safety, quality, and alignment of frontier AI models across policy-sensitive topics. You will assess AI-generated responses, apply safety policies, and help improve model behavior through structured evaluations and feedback.

Responsibilities include evaluating safety and accuracy, reviewing high-risk content, refining evaluation rubrics for RLHF and AI safety benchmarking, and collaborating with research teams to drive safer