Mercor
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A few articles on AI Tutoring:
1) Comparing the various platforms: https://mozibox.com/articles/1769
2) Sharing first-hand experience with Mercor: https://mozibox.com/articles/1472
This role focuses on evaluating and improving how conversational AI systems respond to medical and healthcare topics, ensuring responses are factually correct, clearly explained, and aligned with real-world healthcare knowledge and communication standards. The position involves writing and refining prompts, evaluating AI-generated healthcare responses for accuracy and clarity, and conducting fact-checking using trusted sources.
Key Responsibilities
- • Write and refine prompts to guide model behavior in healthcare scenarios
- • Evaluate LLM-generated responses to healthcare-related queries for accuracy, reasoning, clarity, and completeness
- • Conduct fact-checking of all medical and healthcare claims using trusted public sources and authoritative references
- • Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies
- • Assess tone, completeness, and appropriateness of responses for real-world healthcare use
- • Ensure model responses align with expected conversational behavior and system guidelines
- • Apply consistent evaluation standards by following clear taxonomies, benchmarks, and detailed evaluation guidelines
Required
- • A minimum of 5 years of real-world professional experience in Healthcare
- • An associated expert degree (e.g., MD, DO, RN, NP, PA, PharmD, MPH, or equivalent)
- • Experience in one or more of the following sub-domains: General Clinical Care, Specialty Medicine or Surgery, Diagnostics, Imaging & Laboratory Medicine, Public Health, Healthcare Systems & Administration
- • Significant experience using large language models (LLMs) and understanding how and why people use them
- • Excellent writing communication skills for complex medical topics
- • Strong attention to detail and comfort evaluating clinical reasoning and medical explanations, identifying subtle inaccuracies or gaps
Preferred
- • Prior experience with RLHF, model evaluation, or data annotation work
- • Experience writing or editing high-quality medical or healthcare-related content
- • Experience in clinical documentation, charting, or patient communication, including explaining medical information to non-clinical audiences
- • Familiarity with evaluation rubrics, benchmarks, or quality scoring systems
Company Overview
Industry: Healthcare Technology
Company Size: 500-1,000 employees
Founded: 2015
Headquarters: San Francisco, CA
Company Links
Key Contacts
Contact information not available
About the Company
Leading healthcare technology company focused on improving patient outcomes through innovative digital solutions. We're transforming the way healthcare is delivered with cutting-edge technology and data-driven insights. Our platform serves over 10,000 healthcare professionals and has processed millions of patient interactions.
Recent News & Updates
Fluent Language Skills Required: English
Why This Role Exists
Mercor partners with leading AI teams to improve the quality, usefulness, and reliability of general-purpose conversational AI systems. These systems are used across a wide range of everyday and professional scenarios, and their effectiveness depends on how clearly, accurately, and helpfully they respond to real user questions.
In healthcare-related scenarios, accuracy and clarity are essential. This project focuses on evaluating and improving how conversational AI systems respond to medical and healthcare topics. Your expertise helps ensure responses are factually correct, clearly explained, and aligned with real-world healthcare knowledge and communication standards.
What You’ll Do
Write and refine prompts to guide model behavior in healthcare scenarios
Evaluate LLM-generated responses to healthcare-related queries for accuracy, reasoning, clarity, and completeness
Conduct fact-checking of all medical and healthcare claims using trusted public sources and authoritative references
Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies
Assess tone, completeness, and appropriateness of responses for real-world healthcare use
Ensure model responses align with expected conversational behavior and system guidelines
Apply consistent evaluation standards by following clear taxonomies, benchmarks, and detailed evaluation guidelines
Who You Are
You have a minimum of 5 years of real-world professional experience in Healthcare, supported by an associated expert degree (e.g., MD, DO, RN, NP, PA, PharmD, MPH, or equivalent)
You have experience in one or more of the following sub-domains:
- General Clinical Care
- Specialty Medicine or Surgery
- Diagnostics, Imaging & Laboratory Medicine
- Public Health, Healthcare Systems & Administration
You have significant experience using large language models (LLMs) and understand how and why people use them
You have excellent writing communication skills for complex medical topics
You have strong attention to detail and are comfortable evaluating clinical reasoning and medical explanations, identifying subtle inaccuracies or gaps that others may overlook
Nice-to-Have Specialties
Prior experience with RLHF, model evaluation, or data annotation work
Experience writing or editing high-quality medical or healthcare-related content
Experience in clinical documentation, charting, or patient communication, including explaining medical information to non-clinical audiences
Familiarity with evaluation rubrics, benchmarks, or quality scoring systems
What Success Looks Like
You identify medical inaccuracies, unclear explanations, or unsafe reasoning patterns
Your feedback improves the clarity and reliability of healthcare-related AI responses
You deliver reproducible evaluation artifacts that strengthen model performance
Mercor customers trust their AI systems in healthcare contexts because you’ve rigorously evaluated them
Why Join Mercor
At Mercor, healthcare professionals play a direct role in shaping how AI systems communicate about medical and health-related topics. This role allows you to apply your expertise beyond traditional settings while contributing to the development of more accurate and reliable healthcare AI systems.
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