Data annotation: Accurately label and categorize advanced biology questions, specialized concepts, scientific diagrams, experimental data, and other domain-specific content
Concept mapping: Synthesize and connect complex biological principles, establishing nuanced relationships between specialized topics (e.g., molecular biology, genomics, systems biology, physiology) to help AI models grasp the depth and structure of the field
Solution review: Critically analyze and verify AI-generated answers to advanced biology questions and research-level problems, identifying errors and providing detailed, constructive feedback to enhance model performance
Content development: Design and curate comprehensive training datasets that encompass a wide spectrum of biology subfields and levels of complexity
You’re a great fit if
You hold a PhD in Biology (or a closely related field) with deep expertise in research, teaching, or advanced problem-solving
You have developed or critically reviewed complex scientific, educational, or technical content—such as peer-reviewed publications, advanced curricula, laboratory research, or sophisticated simulations
You excel at communicating challenging physical concepts with clarity and enjoy translating advanced theory into real-world applications
Bonus: Experience with data labeling, RLHF, or other AI training or model evaluation projects
About the role
Flexible workload — work from anywhere, on your own schedule
High impact — your craft directly improves models used by top AI labs & Fortune 500 teams
Clear ownership — know exactly what success looks like and have autonomy to deliver
Growth potential — consistent high performers spearhead new programs and mentor incoming SMEs
Interview process
Complete a screening with Zara, our AI interviewer in English, to learn more about your background and experience.
Domain-specific Zara interview to assess your understanding of advanced Biology principles, your ability to analyze complex processes, and your skill in applying theoretical frameworks to real-world scenarios.