About Us:

Hippocratic AI has developed a safety-focused Large Language Model (LLM) for healthcare. The company believes that a safe LLM can dramatically improve healthcare accessibility and health outcomes in the world by bringing deep healthcare expertise to every human. No other technology has the potential to have this level of global impact on health. 

Why Join Our Team:

• Innovative Mission: We are developing a safe, healthcare-focused large language model (LLM) designed to revolutionize health outcomes on a global scale.

• Visionary Leadership: Hippocratic AI was co-founded by CEO Munjal Shah, alongside a group of physicians, hospital administrators, healthcare professionals, and artificial intelligence researchers from leading institutions, including El Camino Health, Johns Hopkins, Stanford, Microsoft, Google, and NVIDIA.

• Strategic Investors: We have raised a total of $278 million in funding, backed by top investors such as Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems.

• World-Class Team: Our team is composed of leading experts in healthcare and artificial intelligence, ensuring our technology is safe, effective, and capable of delivering meaningful improvements to healthcare delivery and outcomes.

For more information, visit www.HippocraticAI.com.

About the role:

We are seeking meticulous and motivated Data Annotation Specialists to join our team. In this role, you will play a crucial part in enhancing our AI and machine learning initiatives by ensuring the quality, accuracy, and consistency of our datasets. Drawing inspiration from industry-standard practices, including current AI data labeling roles, you will be responsible for data annotation, schedule auditing, and detailed reporting. Your efforts will directly influence the performance of our AI models and contribute to continuous process improvements.

Key Responsibilities:

• Accurately annotate and label large volumes of data—including text, images, and multimedia—to support training and validation of AI models.

• Follow established guidelines and protocols to ensure consistent data quality.

• Assess and verify the accuracy, consistency, and alignment of schedules with established protocols.

• Maintain detailed records of annotations and audit activities.

• Detect scheduling inefficiencies or errors in data processing workflows.

• Proactively highlight discrepancies and recommend corrective actions to improve data integrity and operational efficiency.

• Provide regular updates on annotation progress, quality metrics, and scheduling audits.

• Compile a final summary report with actionable insights to inform stakeholders and guide future process improvements.

• Work closely with data scientists, engineers, and project managers to refine data labeling protocols and enhance overall data quality.

• Participate in team meetings and training sessions to stay updated on best practices and new tools in the data annotation field.

Qualifications:

Must-Have:

• High school diploma or equivalent.

• Strong attention to detail with excellent analytical and problem-solving skills.

• Familiarity with data annotation tools and a willingness to learn new technologies.

• Excellent communication skills and the ability to work collaboratively in a fast-paced environment.

Nice to Have:

• Bachelor’s degree in Computer Science, Data Science, or a related field.

• Prior experience in data annotation, data labeling, or data quality assurance.

• Basic understanding of AI, machine learning, and data processing workflows.