Bioinformatics Problem Designer for AI Training

Help shape the future of AI by designing challenging bioinformatics problems that test and improve reasoning in cutting-edge models.

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.

What you’ll do

• 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

What we’re looking for

• 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

Nice to have

• 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