Train AI on Chemistry Reasoning.
The models shaping the future of AI are only as rigorous as the chemists behind them. Apply your expertise where it matters, and get paid to do it.
Pierre
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This is not busywork.
The largest language models in the world still confuse reaction mechanisms with memorized templates. You're the feedback loop that fixes this — one mechanism at a time.
Three steps.
No overhead.
Apply & Qualify
Complete a short chemistry assessment. We evaluate your ability to reason through reaction mechanisms, identify flawed retrosynthetic analyses, and apply chemical intuition. No resume required — your work speaks.
Get Matched
Based on your background and assessment results, you're matched to projects in your areas of strength. Organic synthesis, computational chemistry, biochemistry, materials science — 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
Craft chemistry prompts designed to probe model reasoning, or review and improve prompts already on the platform. Not trivia, but problems that expose conceptual misunderstandings about bonding, reactivity, and thermodynamics.
Review AI output
Evaluate AI-generated responses to chemistry problems. Identify errors in reasoning, incomplete arguments, and conceptual gaps across a range of difficulty levels and subfields.
Write the correct solution
When a problem requires it, write a complete solution that demonstrates correct chemical reasoning. This helps the model learn what rigorous thinking actually looks like.
Where models need you most.
These are the areas where current AI systems consistently struggle. Your expertise addresses the hardest open problems in chemical reasoning, and your assessment determines where you start, not where you're limited. Contributors regularly work across multiple subfields and difficulty levels.
Organic Synthesis & Retrosynthesis
Evaluate retrosynthetic analyses, multi-step synthesis proposals, and stereochemical outcomes. Check for regioselectivity errors, protecting group logic, and feasibility of proposed transformations.
Physical & Computational Chemistry
Review quantum chemical calculations, thermodynamic derivations, and kinetic analyses. Verify orbital symmetry arguments, transition state geometries, and free energy calculations.
Inorganic & Coordination Chemistry
Assess crystal field theory applications, coordination complex analyses, and organometallic reaction mechanisms. Verify electron counting, symmetry labels, and spectroscopic predictions.
Biochemistry & Chemical Biology
Verify enzyme mechanism proposals, metabolic pathway analyses, and structure-activity relationships. Check for correct protonation states, hydrogen bonding patterns, and catalytic residue identification.
Analytical & Materials Chemistry
Evaluate reasoning about electrochemical systems, polymer behavior, and environmental chemistry applications. Check for errors in reaction feasibility, degradation mechanisms, and quantitative reasoning.
Research-grade standards.
We require excellence, just as you would require in peer review. The researchers and academics on our platform aren’t here to tick boxes. They’re here because the quality standard matters to them.
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“This is evaluation by people who understand system behavior and edge cases. The focus is always on improving model reliability.”
Daniel
Research Engineer
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“Every decision is grounded in first-principles reasoning. The standards are comparable to what I’ve seen in academic and industrial research.”
Anita
Applied Scientist
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“This is annotation done by people who understand models, not just labels. The quality bar is high and enforced.”
Elena
Senior ML Engineer
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“The work demands subject-matter expertise. Decisions are justified, reviewed, and aligned to well-defined taxonomies.”
Stephen
Research Scientist
Chemistry tasks completed weekly
Active chemistry contributors
Subfields represented
Built for people who think in molecules.
Graduate Students
PhD and Master’s candidates in organic, inorganic, physical, or analytical chemistry.
Chemistry Olympiad Competitors
National or international competition experience in chemistry problem solving, including IChO or USNCO level work.
Research Chemists
Active or former researchers applying deep domain knowledge to AI training.
Applied Chemistry Professionals
Engineers with rigorous chemistry foundations working in materials, pharma, or energy.
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.
You’ll work on projects that improve AI systems, such as reviewing responses, checking accuracy, refining prompts, ranking outputs, and validating model behavior.
Projects include data labeling, annotation, evaluation, and quality review across text, images, and structured tasks—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.
This is a flexible, task-based contractor role. There is no long-term commitment required, and you can work as much or as little as you choose.
Available projects vary but commonly include prompt evaluation, response ranking, factual accuracy checks, domain-specific review, and structured annotation tasks.
Researchers, students, professionals, and independent contributors who enjoy analytical work and want to contribute to advancing AI systems.
This is remote, asynchronous work focused on output quality rather than hours logged. Performance is evaluated based on contribution quality and consistency.
Get ahead in a changing workforce.
No recruiters. No interviews. Just meaningful work and real compensation.