AI Safety Evaluation Expert (Remote, Contract)

mercor; Belgique; Remote; EUR 74,000 - 86,000; Part time

Job summary

Mercor is seeking an AI Safety Practitioner to evaluate AI-generated responses for safety, accuracy, policy compliance, and quality, across sensitive domains. You will review misinformation, political persuasion, self-harm, and biosecurity content, and refine RLHF/SFT evaluation rubrics.

The role emphasizes identifying unsafe outputs, hallucinations, and policy violations, followed by structured feedback to improve model alignment and safety performance in collaboration with AI researchers and

Qualifications

• Bachelor's degree or higher in a related discipline (e.g., journalism, communications, psychology, public policy, law, biology, chemistry, CS).
• 5+ years of professional experience in AI Safety, Trust & Safety, journalism, public policy, scientific research, security, or related field.
• Excellent written English; strong critical thinking and analytical reasoning.
• 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

Excellent written English

Critical thinking

Analytical reasoning

Education

Bachelor's degree or higher

Job description

Mercor is seeking an AI Safety Practitioner to evaluate AI-generated responses for safety, accuracy, policy compliance, and quality, across sensitive domains. You will review misinformation, political persuasion, self-harm, and biosecurity content, and refine RLHF/SFT evaluation rubrics.

The role emphasizes identifying unsafe outputs, hallucinations, and policy violations, followed by structured feedback to improve model alignment and safety performance in collaboration with AI researchers and