The customer's team needs to leverage advanced biological knowledge to influence the next generation of AI-driven technologies by training, evaluating, and refining AI models for accuracy, clarity, and comprehensive coverage of biological concepts.
Requirements
- Demonstrated expertise in biological process explanation, from molecular biology to systems-level topics.
- Proven ability to write high-quality, well-structured questions spanning diverse biological domains.
- Strong foundation in core biology concepts, with the ability to convey complex ideas to both technical and non-technical audiences.
- Prior experience in AI model training, data annotation, or EdTech content development.
- Familiarity with the latest advancements in AI/ML as applied to life sciences.
Responsibilities
- Develop and explain complex biological processes in clear, concise, and accurate language to support AI training datasets.
- Create, review, and enhance a wide range of biology questions across multiple domains, ensuring high standards of rigor and relevance.
- Evaluate AI-generated responses and provide expert feedback to improve model accuracy and depth in biology topics.
- Collaborate closely with AI engineers and data scientists to impart domain expertise and contextualize biological content.
- Identify gaps in AI model performance by analyzing response patterns and recommending targeted improvements.
- Maintain up-to-date knowledge of core biology concepts and integrate emerging research into training content.
- Utilize both written and verbal communication skills to articulate feedback, methodologies, and educational materials to interdisciplinary teams.
Other
- Ph.D. or Master’s with significant experience in Biology or a closely related field.
- Exceptional written and verbal communication skills, with a passion for clarity and educational impact.
- Experience collaborating in remote or cross-functional teams.
- Meticulous attention to detail and a commitment to scientific accuracy.
- Track record of interdisciplinary teamwork within scientific and technical environments.
