Advancing artificial intelligence in healthcare and bioengineering by creating, reviewing, and shaping high-impact data used for training cutting-edge AI models.
Requirements
- PhD in Biomedical Engineering or a closely related life sciences/engineering discipline.
- Hands-on experience working with AI/ML applications in healthcare or biomedical research.
- Background in data labeling, content development for education, or prompt engineering for large language models.
Responsibilities
- Develop, annotate, and review sophisticated biomedical engineering content for AI training, including diagrams, images, and academic texts.
- Serve as the subject-matter expert in physiology, bioinstrumentation, and medical device technology, guiding accurate AI model development.
- Create high-quality, educational content tailored for both academic and practical biomedical applications.
- Audit and assess AI-generated biomedical outputs, ensuring scientific rigor, accuracy, and clarity.
- Evaluate and provide feedback on contributions from other domain experts to maintain consistency and quality standards.
- Collaborate with engineers and data scientists to refine annotation tools and processes, driving continuous improvement.
- Offer expert insight to resolve ambiguities and optimize annotation guidelines for biomedical datasets.
Other
- Fluency in English at the CEFR C2 level or higher, with exceptional written and verbal communication skills.
- Comprehensive knowledge of U.S. academic and biomedical standards and practices.
- Demonstrated ability to communicate complex technical concepts clearly and effectively.
- Experience in academic, clinical, or data-intensive environments within biomedical engineering.
- Meticulous attention to detail and unwavering commitment to following guidelines.
- Ability to exercise sound judgment and independent problem-solving in complex or ambiguous scenarios.
