Frontier AI Safety Evaluator & Model Alignment Lead

Obsidian; Amsterdam; On-site; EUR 70,000 - 110,000; Full time

Job summary

Obsidian is seeking experienced AI Safety Practitioners in Amsterdam to evaluate frontier models for safety, quality, and alignment across nuanced topics. You will assess AI-generated responses, apply safety policies, and provide structured feedback to improve model behavior.

The role involves evaluating misinformation, sensitive domains, and applying rubrics for RLHF, SFT, and AI safety benchmarking, with collaboration across AI 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.

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 in a related discipline

Job description

Obsidian is seeking experienced AI Safety Practitioners in Amsterdam to evaluate frontier models for safety, quality, and alignment across nuanced topics. You will assess AI-generated responses, apply safety policies, and provide structured feedback to improve model behavior.

The role involves evaluating misinformation, sensitive domains, and applying rubrics for RLHF, SFT, and AI safety benchmarking, with collaboration across AI researchers and safety teams.