Job Summary: In this role, you’ll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.
Key Responsibilities:
Design, evaluate, and critique biology, bioinformatics, and computational biology workflows to support AI benchmarking initiatives.
Provide expert-level insights on genomic, transcriptomic, proteomic, and other biological data analysis pipelines.
Assess and optimize pipeline parameters, tool configurations, and statistical methods for accuracy and reproducibility.
Analyze biological datasets (e.g., NGS, RNA-seq, single-cell, variant calling, protein structure) and provide actionable recommendations.
Leverage domain knowledge to guide the development and validation of biology-related AI models and tools.
Communicate complex scientific concepts clearly, both in writing and verbally, to technical and non-technical collaborators.
Document findings, methodologies, and best practices to ensure knowledge transfer across the customer’s team.
Areas of Expertise (we welcome applicants from any of the following):
Genomics & NGS analysis
Transcriptomics & single-cell analysis
Proteomics & structural biology
Molecular & cell biology
Systems biology & biological network analysis
Drug discovery & computational pharmacology
Biostatistics & machine learning applied to biology
Required Skills and Qualifications:
PhD in biology, bioinformatics, computational biology, genomics, or a closely related STEM field, or equivalent industry/research experience.
Professional written and spoken English (C1 or higher).
Deep expertise in at least one of the areas listed above, with hands-on experience analyzing real biological data.
Proficiency in Python and/or R for scientific analysis, plus experience with standard tools in your subfield (e.g., BLAST, samtools, GATK, Bioconductor, Biopython).
Strong statistical, quantitative, and analytical reasoning skills.
Outstanding written and verbal communication abilities, with the ability to clearly document and explain technical concepts.
Track record of rigorous scientific problem-solving in complex biological domains.
Preferred Qualifications:
Experience building reproducible workflows (Nextflow, Snakemake) and working in Linux/command-line environments.
Experience with AI/ML-assisted biology workflows or benchmarking.
Peer-reviewed publications, patents, or contributions to open-source bioinformatics software.
