We’re looking for a Clinical AI Safety Contractor to help evaluate how AI systems respond in mental health and other clinically sensitive situations.
You’ll bring clinical judgment to reviewing AI conversations, identifying safety risks, and helping define what appropriate model behavior looks like. This is a flexible, part-time role for clinicians interested in applying their expertise to AI safety and evaluation.
Review and rate AI conversations for clinical safety, appropriateness, and quality
Identify clinically meaningful risks and model failure modes
Help create realistic scenarios, evaluation criteria, and scoring rubrics
Provide expert feedback on how AI should respond in sensitive situations
Participate in calibration and review sessions with researchers and engineers
Document important edge cases and emerging risks
Clinical training and professional credentials are required, such as LCSW/LICSW, LMFT, LPC/LPCC/LCPC, clinical psychologist, psychiatrist, MD/DO, or comparable clinical mental health credentials
Experience working directly with patients or clients in a mental health setting
Strong grounding in clinical assessment, psychopathology, risk evaluation, or crisis response
Strong written communication and clinical judgment
Comfort reviewing sensitive mental health content and maintaining strict confidentiality
No PhD or prior AI experience is required.
Experience with crisis intervention, suicide or self-harm assessment, or safety planning
Experience in adolescent mental health, psychosis, eating disorders, trauma, or other clinically complex areas
Experience developing clinical rating systems, assessment criteria, or coding frameworks
Familiarity with AI, digital mental health, trust & safety, or conversational systems
Vals AI builds rigorous evaluations and benchmarks for frontier AI systems. Our work started from NLP evaluation research at Stanford, and today we work across technical and domain-specific areas, including healthcare and mental health. We’ve raised a $5M seed and our team has backgrounds at Stanford, NVIDIA, Meta, Microsoft, Palantir, HRT, Jane Street, and Snorkel.
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