Train AI, shape the future of biology research
The models shaping the future of AI are only as rigorous as the biologists behind them. Apply your expertise where it matters, and get paid to do it.
Grace
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This is not busywork.
The most advanced language models still hallucinate enzyme mechanisms, confuse taxa, and invent gene functions. You're the biological filter that catches what machines can't — one annotation at a time.
Three steps.
No overhead.
Apply & Qualify
Complete a short biology assessment. We evaluate your ability to interpret experimental data, identify flawed biological reasoning, and apply mechanistic thinking. No resume required — your knowledge speaks.
Get Matched
Based on your background and assessment results, you're matched to projects in your areas of strength. Molecular biology, genomics, ecology, neuroscience, biochemistry; you choose what fits.
Work & Get Paid
Complete tasks on your own schedule. Each task has clear specifications and a defined scope. Payment is per-task, processed weekly, starting at $40/hour.
What you'll actually do.
Write a prompt
Ask questions that test the model's understanding across biological disciplines.
Review AI output
Evaluate model-generated answers line by line. Identify misattributed gene functions, confused signaling pathways, and incorrect interpretations of experimental data.
Evaluate the model's response for scientific accuracy.
Write the correct solution
Author a complete, rigorous response that demonstrates the correct biological reasoning. This becomes training signal for the next model generation.
Provide an answer that reflects the standard of peer-reviewed literature.
Where models need you most.
These are the areas where current AI systems consistently struggle. Your expertise directly addresses the hardest open problems in biological reasoning.
Proof-Based Reasoning
Evaluate and construct formal biological arguments. Identify logical gaps, invalid inferences, and incomplete mechanistic reasoning in model-generated explanations.
Multi-Step Problem Solving
Review complex biological processes requiring sequential reasoning. Check that each step follows validly from the last and that no intermediate mechanisms are skipped.
Symbolic Logic & Formalization
Assess the model's ability to translate natural language into formal biological frameworks and reason within established scientific systems.
Edge Cases & Counterexamples
Identify where models fail on edge cases, degenerate biological scenarios, and subtle counterexamples that break general claims.
Quantitative Modeling
Evaluate applied biology problems involving experimental design, statistical reasoning, and biological modeling of real-world systems.
A selective community of experts
Work alongside writers, lawyers, health professionals, coders, professors, and bilingual experts shaping the future of AI.
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The problems here actually require engineering judgment. It's some of the most rigorous work I've done outside of a staff role.
Marcus
Software Engineer
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The variety is what I didn't expect. One week I'm rewriting technical explanations, the next I'm evaluating how a model handles tone and voice.
Julia
Senior Copywriter
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Clinical nuance matters in this work. It's rare to find contract work where my specialty actually gets used properly.
Melissa
Clinical Reviewer
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The evaluation work here is more rigorous than most PM research I've run in-house. I've genuinely changed how I think about product quality.
Azhar
Senior Product Manager
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Legal reasoning in AI is still an unsolved problem. Getting to shape how these models handle it, from a practitioner's perspective, is the work I actually want to be doing.
Krysta
Solicitor
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The code review standards here are higher than most teams I've worked on. It's sharpened how I think about edge cases in my day job.
Tyler
Senior Engineer
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Pressure-testing these tools surfaces failure modes that matter. The work holds up to the standards I'd apply in practice.
Abi
Litigation Attorney
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Most freelance work in my field is content mills. This is the first engagement where my clinical training is the reason I was hired, not an afterthought.
Liana
Clinical Researcher
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My writing background is exactly what this work needs. Evaluating how models handle narrative, voice, and subtext is surprisingly rigorous.
Mi Ji
Screenwriter
Paid to contributors
Expert annotators
Annotations completed
Built for people who think in theories.
Graduate Students
PhD and Master's candidates in molecular biology, cell biology, or related life sciences.
Olympiad Competitors
National or international competition experience in biological problem solving.
Research Biologists
Active or former researchers applying deep expertise to AI reasoning.
Applied Biology Professionals
Clinicians, biotech professionals, and data scientists with rigorous biological foundations.
Frequently Asked Questions
Have questions? Here we answer the most common questions.
You'll work on tasks that help AI perform better, like reviewing responses, checking accuracy, refining prompts, and rating outputs. No coding or technical background needed.
Projects vary but commonly include reviewing AI-generated text, ranking responses, checking facts, labeling data, and reviewing content in specific subject areas. All focused on improving real production AI systems.
This is ideal for people with strong reasoning skills, attention to detail, and subject-matter expertise who want flexible, remote work with real impact. Researchers, students, professionals, and independent contributors who enjoy analytical work and want to contribute to advancing AI systems.
This is a flexible, task-based contractor role. You work remotely on your own schedule, focused on output quality rather than hours logged. There is no long-term commitment required, and you can work as much or as little as you choose.
Get ahead in a changing workforce.
No recruiters. No interviews. Just meaningful work and real compensation.