Frontier AI Safety Evaluator

Mercor; Stockholms kommun; Remote; SEK 700,000 - 1,100,000; Full time

Job summary

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

Responsibilities include evaluating outputs for safety across sensitive domains, refining RLHF/SFT rubrics, and providing actionable feedback to researchers and safety teams.

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 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

Written English

Critical thinking

Analytical reasoning

Policy sensitivity

Education

Bachelor's degree or higher in related field

Tools

RLHF

SFT

AI evaluation

Job description

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

Responsibilities include evaluating outputs for safety across sensitive domains, refining RLHF/SFT rubrics, and providing actionable feedback to researchers and safety teams.