Experimental Biologist (Generative Genomics)

Location: San Francisco, United States. Must be authorized to work in the U.S.; the company participates in E-Verify.

Company

hirify.global is an AI research lab developing generative biological models and generative genomics to advance scientific understanding, drug discovery, and biological defense.

What you will do

• Design experiments testing predictions, molecules, sequences, and biological systems generated or prioritized by AI models.
• Work with ML researchers and computational biologists to translate modeling questions into fast, informative experiments.
• Analyze experimental results, troubleshoot failures, and select high-value follow-up experiments.
• Identify and manage CROs, academic laboratories, core facilities, and other experimental partners across multiple programs.
• Develop experimental plans, protocols, budgets, timelines, controls, success criteria, and data-quality standards.
• Design closed-loop workflows in which models propose designs, experiments test them, and resulting data improves future models.
• Help decide which capabilities to outsource or build internally, establish wet-lab infrastructure and workflows, and eventually recruit and manage an experimental team.

Requirements

• PhD or equivalent research experience in experimental biology, bioengineering, molecular biology, cancer biology, synthetic biology, or a related field.
• Independent experience designing, executing, and troubleshooting rigorous wet-lab experiments.
• Experience with high-throughput or pooled systems such as CRISPR screens, MPRAs, or related approaches.
• Experience managing CROs, core facilities, or academic collaborators, including protocols, controls, budgets, timelines, and data quality.
• Ability to interpret experimental results and communicate with both experimental and computational researchers.
• U.S. work authorization is required.

Nice to have

• Experience in cancer biology, functional genomics, protein engineering, synthetic biology, virology, or therapeutic development.
• Experience generating experimental datasets for machine learning or AI.
• Experience building or scaling a wet lab and managing research staff.
• Experience in an early-stage biotech or highly interdisciplinary research organization.

Culture & Benefits

• Hands-on role combining scientific strategy, experimental execution, and operational ownership.
• Opportunity to build experimental capabilities and laboratory infrastructure from the ground up.
• Close collaboration across biology, machine learning, computational biology, and numerics research.
• Work focused on developing both biological design capabilities and responsible defenses against engineered threats.