Senior Scientist - Virology (Science)

TL;DR

Senior Scientist - Virology (Science): Conducting wet-lab experiments and designing reverse genetics-based plasmid virus production systems with an accent on assay development and protocol optimization. Focus on collaborating with AI and data engineers to build infrastructure for reproducible science and capturing tacit laboratory knowledge.

Location: On-site, Cambridge, MA (Kendall Square); no flexibility for remote or hybrid work

Salary: $45-75/h

Company

hirify.global is building physical AI to make real-world scientific work legible, transferable, and reproducible.

What you will do

• Design and implement reverse genetics systems for multiple virus families.
• Design, perform, and optimize molecular and virology assays, including plaque assays, reporter assays, RT-qPCR, and cloning.
• Support documentation and systematic troubleshooting to enhance workflow reproducibility.
• Collaborate with AI, biology, and data engineers to build the infrastructure behind fast, reproducible science.
• Uphold rigorous BSL-2 safety standards.

Requirements

• PhD, or MS with 3+ years experience, or BS with 5+ years experience in Virology, Molecular Biology, or related fields.
• Hands-on lab experience with viral reverse genetics systems and plasmids.
• Located within commuting distance from Cambridge, MA.
• Strong bias toward documentation, reproducibility, and iteration in experimental design.
• Ability to communicate technical concepts clearly to cross-functional teams.

Nice to have

• Startup or early-stage experience with comfort in ambiguity.
• Coding experience in Python or R for complex data analysis.
• Experience using AI/ML tools for experimental design or predictive modeling.
• Direct customer-facing work in partner or external lab environments.

Culture & Benefits

• Early-stage startup environment with rapid iteration.
• Opportunity to work at the intersection of physical AI and laboratory science.
• High-impact role focused on building the world's largest commercial dataset on scientific execution.