The candidate will review medical records and clinical documentation to validate coding accuracy and identify discrepancies. They will also provide expert feedback to improve the accuracy of AI models used in medical coding and documentation evaluation.
The Clinical Pharmacist will support an AI training project by reviewing medication-related clinical scenarios and evaluating AI-generated pharmacy recommendations. Responsibilities include identifying medication errors, reviewing clinical treatment plans, and providing expert feedback to improve AI model performance.
Annotate and classify food items, portion sizes, and dietary patterns to evaluate AI-generated content for accuracy and safety. Maintain quality benchmarks and refine annotation guidelines for diverse dietary contexts.
Annotate and classify sleep-related data such as stages, duration, and quality indicators to evaluate AI model outputs. Identify patterns and anomalies in sleep logs and sensor data to ensure scientific accuracy and safety in AI-generated content.
The role involves authoring and evaluating high-fidelity clinical tasks, long-chart scenarios, and workplace simulations to serve as benchmarks. Specialists will also perform peer reviews, calibrate work across teams, and ensure clinical accuracy and regulatory alignment.
