Help shape the future of AI by designing challenging bioinformatics 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
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 Bioinformatics 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.
Design advanced bioinformatics 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 sequence analysis, genomics, transcriptomics, proteomics, phylogenetics, or computational biology
Build tasks that require interpretation of biological data and multi-step computational reasoning
Where relevant, use Python, R, command-line bioinformatics tools, or specialized computational workflows to validate solutions
Ensure all outputs are technically precise, reproducible, and well-written in English
Master’s or PhD in Bioinformatics, Computational Biology, Genomics, or a closely related field
Strong research or industry experience working with biological datasets and computational analysis
Strong Python and/or R skills
Experience with sequence analysis, statistical methods, algorithms, and reproducible computational workflows
Ability to design original, difficult problems that mirror real bioinformatics workflows
Excellent attention to detail and technical writing skills in English
Experience with Biopython, Bioconductor, BLAST, SAMtools, BWA, GATK, Nextflow, Snakemake, or similar tools
Background in next-generation sequencing, single-cell analysis, structural bioinformatics, or machine learning for biology
Experience with benchmark design, scientific dataset curation, or evaluating AI systems on biological reasoning