Research Scientist (AI)

Location: San Francisco, United States; hybrid workplace

Company

hirify.global builds frontier AI models that computationally design medicines and novel proteins, combining generative AI with experimental biology.

What you will do

• Design, execute, optimize, and troubleshoot cell-based and biochemical assays for model-generated proteins.
• Develop high-throughput, plate-based workflows and establish new experimental capabilities with technical consultants.
• Improve screening throughput, reproducibility, and efficiency in collaboration with automation specialists.
• Process, analyze, and interpret experimental data using Python and Jupyter notebooks; define controls and QC criteria.
• Document methods, samples, conditions, and results in Benchling, a LIMS, or comparable systems.
• Work with ML researchers to connect experimental findings and biological context to subsequent protein-design cycles.

Requirements

• PhD in molecular biology, cell biology, biochemistry, or a related field.
• At least 1–3 years of relevant industry research experience for Scientist roles; more than 3 years for Sr. Scientist roles.
• Ability to take an assay from feasibility testing through optimization and reproducible execution.
• Experience developing or running high-throughput experiments, ideally with plate-based assays and laboratory automation.
• Strong molecular biology and mammalian cell culture experience, with relevant methods such as molecular cloning, cell-based functional assays, flow cytometry/FACS, ELISA, or next-generation sequencing. Expertise in every listed technique is not required.
• Proficiency in Python and Jupyter notebooks for reproducible data processing, analysis, and visualization.
• Experience maintaining experimental records and using Benchling, a LIMS, or comparable sample and data tracking tools.
• Depth in at least one technical area: gene editing and protein–DNA interaction characterization; membrane protein characterization; or protein biochemistry and biologics characterization. Expertise across all three areas is not expected.

Nice to have

• Experience in an early-stage biotech and in establishing new assays, workflows, or laboratory processes.
• Experience transferring consultant-developed or externally developed assays into an internal laboratory.
• Experience improving automated screening workflows or sample and data management systems.
• Familiarity with Git and GitHub for version control and collaborative analysis.
• Experience working with computational scientists or evaluating computationally designed proteins.
• For Sr. Scientist roles: experience mentoring others, additional industry experience, and managing complex CRO projects, including SOW review, contract negotiation, and troubleshooting.

Culture & Benefits

• Work at the intersection of generative AI, computational biology, and experimental drug discovery.
• Collaborate with experimental scientists, ML researchers, automation colleagues, and technical expert consultants.
• Contribute to research targeting novel proteins and computationally designed medicines.
• Competitive compensation, equity, and benefits.
• Opportunity for significant ownership and impact in a rapidly expanding early-stage biotech.