Frontier AI Safety Evaluator

Mercor; Oslo; Remote; NOK 700,000 - 1,000,000; Full time

Job summary

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

The role involves collaborating with AI researchers and safety teams to refine rubrics for RLHF, SFT, and safety benchmarking, with a focus on identifying unsafe outputs and policy violations in complex scenarios.

Qualifications

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

Responsibilities

• 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.

Skills

AI Safety

Policy Evaluation

Critical Thinking

Analytical Reasoning

English Writing

Education

Bachelor's degree or higher in related field

Job description

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

The role involves collaborating with AI researchers and safety teams to refine rubrics for RLHF, SFT, and safety benchmarking, with a focus on identifying unsafe outputs and policy violations in complex scenarios.