Senior AI Safety & Clinical QA Lead (Remote)

mpathic; Oregon; Hybrid; USD 140,000 - 170,000; Full time

Benefits offered by this job

Equity

Health, dental, and vision insurance

401(k) with 4% company match

Well-being programs

Remote-first work environment

Flexible paid time off

Job summary

mpathic is seeking a Senior Clinical Safety Lead to support high-quality annotation, labeling, red teaming, and AI safety evaluation across sensitive human data projects. This remote, full-time role reports to the Human Data / AI Safety leadership and partners with product, engineering, and customer delivery to ensure clinically grounded, auditable outputs.

The role emphasizes rubric-based evaluation, reviewer training, calibration, and escalation for edge cases while maintaining safety

Qualifications

• 5+ years of experience in clinical supervision and safety evaluation.
• Experience writing research reports with clinical nuance.
• Ability to train experts on rubrics, taxonomies, and labeling schemes.

Responsibilities

• Review annotated datasets for clinical appropriateness, label consistency, and safety alignment.
• Serve as escalation point for ambiguous labels and edge cases.
• Develop and deliver reviewer training, calibration, and guidance materials.
• Build and improve QA workflows, rubrics, and taxonomies for evaluation projects.
• Collaborate cross-functionally to ensure interpretable and trustworthy customer reporting.

Skills

Clinical supervision

Annotation QA

Rubric-based evaluation

Training reviewers

Quality review

Education

Clinical licensure

Advanced clinical training (PsyD/PhD/MD)

Job description

mpathic is seeking a Senior Clinical Safety Lead to support high-quality annotation, labeling, red teaming, and AI safety evaluation across sensitive human data projects. This remote, full-time role reports to the Human Data / AI Safety leadership and partners with product, engineering, and customer delivery to ensure clinically grounded, auditable outputs.

The role emphasizes rubric-based evaluation, reviewer training, calibration, and escalation for edge cases while maintaining safety