ABOUT THE ROLE:
We are seeking a dedicated AI Healthcare and Administration Data Specialist to enhance xAI’s AI models by providing high-quality data annotations and inputs tailored to healthcare and administration contexts. In this role, you will leverage your expertise in patient care coordination, medical billing, administrative workflows, and healthcare operations to support the training of AI systems. You will collaborate with technical teams to refine annotation tools and curate impactful data, ensuring our models effectively capture real-world healthcare and administrative dynamics. This role requires adaptability, strong analytical skills, and a passion for driving innovation in a fast-paced environment.
RESPONSIBILITIES:
- Utilize proprietary software to provide accurate input and labels for healthcare and administration projects, ensuring high-quality data for AI model training.
- Deliver curated, high-quality data for scenarios involving patient care coordination, medical billing, administrative workflows, and healthcare operations.
- Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies.
- Assist in designing and improving efficient annotation tools tailored for healthcare and administration data.
- Select and analyze complex problems in healthcare and administration fields aligned with your expertise to enhance AI model performance.
- Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.
BASIC QUALIFICATIONS:
- Professional experience in healthcare administration or related fields (e.g., medical and health services manager, medical secretary, or administrative assistant).
- Proficiency in reading and writing informal and professional English.
- Strong communication, interpersonal, analytical, and organizational skills.
- Excellent reading comprehension and ability to exercise autonomous judgment with limited data.
- Passion for technological advancements and innovation in healthcare and administration processes.
PREFERRED SKILLS AND EXPERIENCE:
- Relevant certification or training (e.g., Certified Medical Manager, Certified Professional in Healthcare Management, or similar administrative certification).
- Experience mentoring or training others in healthcare administration or operational practices.
- Comfort with recording audio or video sessions for data collection.
- Familiarity with AI or data annotation workflows in a technical setting.
LOCATION AND OTHER EXPECTATIONS:
- Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
- For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
- Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
- For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
- We are unable to provide visa sponsorship.
- For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.
COMPENSATION AND BENEFITS:
US based candidates: $45/hour - $100/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.
Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.
