Teams at Sequencing.com

Lead evaluation and benchmarking of AI-driven genomic interpretation: own gene/disease/variant mapping logic, define accuracy and release criteria, establish regression standards, partner on automated validation, and guide where deterministic logic supplements models.

Design, implement, and run automated benchmarking and validation pipelines for AI-driven genomic interpretation. Expand regression datasets, execute large-scale validation across curated VCFs, surface accuracy regressions, build automated QA for AI releases, and integrate validation into CI/CD with dashboards and documented failure modes.

Design, build, and maintain scalable production pipelines and services to process clinical-grade whole genome data. Optimize performance, reliability, and cost on AWS, support VCF/BAM/FASTQ and consumer-scale genomic datasets, develop tools in Python/C#/SQL, use containers and orchestration, collaborate across teams, debug infrastructure issues, and deliver validated genetic insights.