Frontier AI Safety Evaluator & Policy Auditor

Obsidian; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Obsidian 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, apply safety policies, and help improve model behavior through structured evaluations and feedback.

Responsibilities include evaluating responses for safety, factual accuracy, and policy compliance; reviewing high-risk content; and collaborating with AI researchers on ongoing evaluation initiatives.

Qualifications

• Bachelor's degree or higher in journalism, communications, psychology, public policy, or related field.
• 5+ years of professional experience in AI safety, trust & safety, policy, or research.
• Excellent written English and strong analytical reasoning.
• Ability to evaluate nuanced, 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

Quality evaluation

Education

Bachelor's degree or higher

Job description

Obsidian 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, apply safety policies, and help improve model behavior through structured evaluations and feedback.

Responsibilities include evaluating responses for safety, factual accuracy, and policy compliance; reviewing high-risk content; and collaborating with AI researchers on ongoing evaluation initiatives.