Senior AI Safety Evaluator

Mercor; Dublin; Remote; EUR 90,000 - 130,000; Full time

Job summary

Mercor in Ireland 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 and provide structured feedback to improve model behavior.

You will collaborate with AI researchers and safety teams on ongoing evaluation initiatives, review content across sensitive domains, and help refine evaluation rubrics for RLHF, SFT, and benchmarking.

Qualifications

• Bachelor’s degree or higher in a relevant 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

Critical thinking

Analytical reasoning

Excellent written English

Policy evaluation

AI safety knowledge

Education

Bachelor's degree or higher in a relevant field

Job description

Mercor in Ireland 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 and provide structured feedback to improve model behavior.

You will collaborate with AI researchers and safety teams on ongoing evaluation initiatives, review content across sensitive domains, and help refine evaluation rubrics for RLHF, SFT, and benchmarking.