Help shape the future of AI by designing challenging genetics problems that test and improve reasoning in cutting-edge models.
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. Our data is used directly in training and evaluation pipelines at leading AI labs to improve model reasoning in technical domains.
We are looking for experts in Genetics to design rigorous, deterministic problems that are genuinely challenging for state-of-the-art AI systems. Each problem must have exactly one verifiable correct answer and be submitted together with a complete, verified solution.
WHAT YOU'LL DO:
Design advanced genetics problems for frontier AI training and evaluation
Create deterministic problems with exactly one correct answer
Write complete, verified solutions and clearly document the reasoning process
Develop problems involving Mendelian genetics, population genetics, molecular genetics, quantitative genetics, genomics, or genetic variation
Create problems requiring multi-step interpretation of inheritance patterns, experimental data, pedigrees, or genomic information
Where relevant, use Python, R, statistical software, or genetics-specific computational tools to validate solutions
Ensure all outputs are technically precise, reproducible, and well-written in English
WHAT WE'RE LOOKING FOR:
Master's or PhD in Genetics, Genomics, Molecular Biology, Computational Biology, or a closely related field
Strong research or industry experience involving genetics, genomics, molecular biology, or quantitative genetic analysis
Strong quantitative reasoning and data-analysis skills
Solid understanding of inheritance, genetic variation, experimental design, probability, and statistical genetics
Ability to design original, difficult problems that mirror real genetics research workflows
Excellent attention to detail and technical writing skills in English
NICE TO HAVE:
Experience with R, Python, PLINK, GATK, bcftools, Bioconductor, or other genomics and genetics tools
Background in population genetics, GWAS, quantitative genetics, functional genomics, or molecular genetics
Experience designing scientific assessments, analyzing research datasets, or evaluating AI reasoning in life-science domains
