Job details
About this role
Role overview Contribute to advanced AI training and evaluation by authoring rigorous, deterministic genetics problems used to test and improve frontier model reasoning. The position is a remote, part-time contract focused on producing high-quality STEM problem sets for an AI data project, with each item requiring a single verifiable answer and a complete solution.
Responsibilities - Author genetics problems spanning Mendelian, population, molecular, and quantitative genetics, as well as genomics and genetic variation - Build exercises that demand multi-step reasoning over inheritance patterns, pedigrees, experimental datasets, and genomic information - Produce fully worked, verified solutions with clear documentation of the reasoning chain - Validate answers using Python, R, statistical packages, or genetics-specific computational tools where applicable - Maintain technical precision, reproducibility, and clear English writing across all deliverables
Requirements - Master's or PhD in Genetics, Genomics, Molecular Biology, Computational Biology, or a closely related discipline - Demonstrated research or industry experience in genetics, genomics, or quantitative genetic analysis - Strong quantitative reasoning and data-analysis capabilities - Solid grounding in inheritance, genetic variation, experimental design, probability, and statistical genetics - Ability to design original, research-grade problems that mirror authentic lab workflows - Excellent attention to detail and technical writing skills in English
Nice to have - Hands-on experience with R, Python, PLINK, GATK, bcftools, or Bioconductor - Background in population genetics, GWAS, quantitative genetics, functional genomics, or molecular genetics - Prior work designing scientific assessments or evaluating AI reasoning in life-science contexts
Benefits and work setup - Remote contract, approximately 20 hours per week, up to 40 USD per hour - Two-month initial project with potential extension and immediate start availability