Child & Adolescent Mental Health AI Safety Advisor

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We connect expert contributors with meaningful, paid work that shapes how AI behaves, and we support freelancers as they build unified portfolios of experience.

Why AI training matters

AI models learn from examples and human judgment. This role places you at the human side of model safety—helping ensure conversational agents interact with adolescents in ways that are clinically responsible and ethically sound.

These projects are often remote and flexible, and they let clinicians directly influence safety standards for digital mental health tools.

• Work that directly shapes AI behavior around sensitive youth mental health issues
• Flexible, remote contracting work suitable for experienced clinicians and researchers

The role

OpenTrain AI is hiring a Child & Adolescent Mental Health AI Safety Advisor to create and validate clinician-informed benchmarks for evaluating AI companion chatbots. You will translate clinical judgment into rigorous evaluation standards used to assess model outputs for safety and ethical risk.

• Write fictionalized adolescent mental health case scenarios with clinical realism
• Review AI-generated conversations for suicide risk, therapeutic impersonation, parasocial attachment, and other sensitive behaviors
• Refine evaluation rubrics and help calibrate automated systems using expert judgment

What you'll do (key responsibilities)

Work with the OpenTrain team to develop robust, defensible evaluation materials and ratings that reflect real-world adolescent clinical concerns.

• Author adolescent mental health case scenarios that feel clinically realistic and developmentally appropriate
• Review scenarios and AI-generated conversations for safety, ethics, and response quality
• Help develop and refine evaluation rubrics for chatbot behavior
• Calibrate automated evaluation systems with expert judgment on high-risk responses
• Advise on best practices for assessing suicide risk, treatment advice, emotional dependency, and discouraging inappropriate trusted relationships

Required qualifications

You must be an experienced clinician or researcher with demonstrated expertise in child and adolescent mental health and the ability to provide clear, structured written feedback.

• MD, DO, PhD, PsyD, or equivalent training in psychiatry, psychology, or a related mental health field
• Clinical or research experience focused on children and adolescents
• Experience with suicide prevention, self-harm assessment, child and adolescent psychiatry, clinical child psychology, digital mental health, DBT, or CBT
• Strong written communication and the ability to provide structured clinical feedback
• Comfort reviewing fictional clinical scenarios and AI-generated conversations

Preferred experience

The project benefits from people who have worked at the intersection of clinical care, research, and digital health product evaluation.

• Experience with suicide risk assessments or crisis intervention
• Academic or published research in adolescent mental health, suicide prevention, or digital therapeutics
• Experience developing clinical guidelines, assessment frameworks, or educational materials
• Prior work evaluating AI, digital health technologies, or mental health products
• Experience supervising trainees or working on multidisciplinary clinical teams

Time, pay, and logistics

Compensation is paid hourly with a range of $80–$150 USD per hour based on expertise and role needs. This is a contract, part‑time position for OpenTrain AI contributors.

• Typical weekly commitment noted in the role text is approximately 10–15 hours per week; the posting metadata also lists 20+ hours/week—please ensure your availability matches the level you apply for
• Employment type: Contractor, Part-time
• Location & language: United States-based contributors, English required

How to apply

Create or update your OpenTrain profile and submit your application noting your clinical background, relevant publications or programs, and availability. Your submission should highlight child/adolescent work and experience with suicide risk assessment or digital mental health evaluation.

• Include examples of relevant research, clinical programs, publications, or prior evaluation work when possible
• Be prepared to provide structured writing samples or sample scenario reviews if requested