Biology AI Training Expert (Ecuador)
Department: STEM
Location: Ecuador - Fully Remote
Compensation: $0 – $40 per hour
Employment Type: Contract
Location: Remote
Type: Contract / Part-time
Commitment: 20 hours per week
Compensation: Up to 40 USD / hr
Project duration: 2 months, with potential extension
Availability: Immediate start
About the role
We create high-quality STEM training data for frontier AI models used by leading AI labs to improve model reasoning in scientific domains.
We are seeking experts in Biology to create challenging, deterministic problems with exactly one verifiable correct answer. Problems should reflect authentic scientific and analytical workflows and be submitted with complete, verified solutions.
Depending on specialization, work may include molecular biology, genetics, systems biology, computational biology, bioinformatics, or adjacent quantitative biology fields.
What you’ll do
Design advanced biology problems that challenge frontier AI systems
Create deterministic tasks with one correct answer
Submit complete, verified solutions
Build problems involving experimental reasoning, biological systems, computational analysis, or bioinformatics workflows
Use Python and, when relevant, specialized biology or bioinformatics tools
Ensure high standards of rigor, reproducibility, and technical clarity
What we’re looking for
Bachelor's, Master’s or PhD in Biology or a related life sciences field
Research or industry experience involving computational or quantitative biological analysis
Strong Python skills; experience with data analysis or bioinformatics workflows preferred
Strong reasoning ability and comfort with multi-step scientific problem solving
Ability to create original, difficult problems grounded in real biological practice
Clear written English and strong attention to detail
Nice to have
Experience with bioinformatics toolkits, genomics workflows, structural biology tools, or computational biology methods
Experience designing technical assessments or scientific challenge problems
Cross-disciplinary experience spanning biology and computation
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