Science-focused Member of Technical Staff (Generative Genomics)

Location: San Francisco, United States; on-site

Company

hirify.global is an AI research lab building general biological intelligence and generative biological models from large-scale scientific data.

What you will do

• Source, normalize, curate, and steward genomic, epigenomic, transcriptomic, proteomic, and imaging datasets with rigorous metadata and provenance.
• Build evaluation suites and benchmarks to stress-test generative biological models across modalities and tasks.
• Analyze model outputs, run ablations, debug unexpected behavior, and identify insights that inform architecture and training improvements.
• Integrate datasets and annotations from external collaborators while maintaining compliance, privacy, and ethical standards.
• Co-develop filters and validation pipelines with AI engineering peers and communicate scientific findings across the organization.

Requirements

• PhD in genetics, computational biology, or a related field, or 3+ years of impactful biotech experience.
• Experience curating, harmonizing, and analyzing large biological datasets, including genomics, single-cell, spatial, or imaging data.
• Fluency with Python, data tooling, Git, notebooks, containers, and reproducible workflows.
• Ability to interrogate model outputs and translate findings into actionable recommendations.
• Strong communication skills for bridging scientific context with engineering teams and partner organizations.
• Must be authorized to work in the United States; the company participates in E-Verify.

Nice to have

• Experience with generative model evaluation, red-teaming, or safety analysis in scientific domains.
• Experience with statistical validation, quality control, or benchmarking for scientific or ML systems.
• Experience building benchmarking frameworks or open datasets adopted as community standards.
• Contributions to shared analytics tooling or reproducible research pipelines.

Culture & Benefits

• Work on multimodal biological world models supporting detection, response, and countermeasures in global health.
• Collaborative, cross-disciplinary environment spanning AI labs, biotechs, hospital systems, and national research institutes.
• Culture focused on rigor, creativity, and scientific responsibility.
• Competitive compensation, comprehensive benefits, and support for continual learning.