Requirements

• At least 8 months of hands-on experience in data labeling, annotation, AI training or evaluation, content quality, or a similar operational environment.
• Basic understanding of artificial intelligence and machine learning concepts, particularly how high-quality training data influences model performance.
• Bachelor's degree or higher in medicine or a clinical/medicine-adjacent discipline such as medicine, nursing, public health, health administration, or biomedical engineering; relevant graduate degrees such as an MPH or MHA are also applicable.
• Alternatively, 5+ years of relevant professional experience may be considered in place of a degree.
• Previous people-management or team-leadership experience is preferred.
• Medical Doctorate (MD, DO, MBBS, or equivalent) or another completed clinical doctoral qualification, such as PharmD, DDS, or certain PhDs, is highly desirable.
• Residency or postgraduate clinical experience is a plus, as is familiarity with clinical data and workflows involving laboratory results, medical imaging, electronic health records, and clinical documentation.
• Demonstrated ability to review domain-specific work, maintain high data-quality standards, and improve operational processes.
• Experience with performance management, coaching, training programs, or certification frameworks.
• Strong analytical capabilities and experience using data and KPIs to drive operational improvements; SQL knowledge is a plus.
• Experience managing distributed teams or teams comprising different employment types, including employees and contractors.
• Excellent written and verbal communication skills, with the ability to build relationships, communicate clearly, and align diverse stakeholders.
• Familiarity with project management and collaboration tools such as Notion, Axiom, JIRA, Linear, or equivalent platforms.
• Strong organizational skills, attention to detail, proactive problem-solving abilities, and a continuous-improvement mindset.
• Ability to combine strategic thinking with hands-on execution and maintain high standards in a rapidly changing environment.
• Passion for developing high-performing teams and scaling reliable, high-quality Human Data operations.

Benefits

• Competitive compensation, with international salary details provided during the recruitment process.
• For eligible U.S.-based positions, base salary ranges from $104,000 to $170,400 USD, depending on experience, skills, education, location, and qualifications.
• Equity opportunities as part of the overall rewards package.
• Comprehensive medical, dental, and vision coverage, subject to employment type, location, and local regulations.
• Access to a 401(k) retirement plan for eligible U.S.-based positions.
• Short- and long-term disability insurance.
• Life insurance.
• Paid sick leave for eligible U.S.-based positions.
• Additional employee discounts and perks.
• Opportunity to work remotely where permitted and contribute to a globally distributed organization.
• Opportunity to work at the intersection of medicine, human data, and advanced AI development.
• Collaborative, high-autonomy environment focused on curiosity, engineering excellence, and continuous learning.

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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