Youth Mental Health AI Trainer (Behavioral Health)
About the role
Addiction counselors, psychologists, guidance counselors and other clinicians who work with teens can help train AI to assess adolescent substance use cases. You'll review cases and write clear guidance on risk, severity and the right level of care. No AI experience is needed; your clinical knowledge is what counts. Remote contract work. Click Apply to open the micro1 page, sign up there using this link, and micro1 handles screening and hiring. AI Alerts may earn a referral fee if you're hired through this link. It costs you nothing and doesn't change how we pick or rank jobs.
What you'll do
- Review and improve how AI responds to teen substance use cases
- Review adolescent substance use cases and document risk, severity and how urgent the response is
- Apply frameworks such as DSM 5 and ASAM to recommend a level of care
- Check the safety of proposed and alternative interventions
- Tell normal experimentation apart from clinically significant substance use
- Flag withdrawal, overdose and safeguarding risks that need escalation
- Write clear guidance that non specialists can follow
Requirements
- Preferred: 3 to 5+ years of post certification experience working directly with adolescents impacted by substance use
- Preferred: Clinical specialty in addiction medicine, or child/adolescent psychiatry or psychology with a primary focus on substance use disorders
- Preferred: Active clinical license/registration in good standing, with recent (<2 years) adolescent caseload experience
- Preferred: Research standard written English (native, or IELTS 7.5+ overall/writing 7.0+, TOEFL 100+, Cambridge C1 to C2, or equivalent)
- Familiarity with screening tools such as CRAFFT and S2BI, and with DSM 5 and ASAM criteria
- Selection: micro1 screens applicants and handles hiring
About micro1
micro1 is a data lab that helps AI labs and large companies train AI models and agents. It finds and checks skilled people from many fields, like law, medicine, finance and coding, to produce the training data that makes AI work better.
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