Senior Scientist – Virology (Contractor)

Location: On-site, Cambridge MA (Kendall Square); no flexibility for remote or hybrid work
Hours: Part-time (20h/week) and full-time (40h/week) contracts under consideration
Temporary: Fixed 8-12 week term, starting as early as May 15, 2026
Salary: $45-75/h (pay is based on a 40 hour per week schedule and depends on experience/expertise)
Level: Subject Matter Expert (PhD or 5+ years of relevant industry experience)

About Transfyr

Transfyr is building physical AI for science.

Why is it that a professional athlete has dramatically more information about every play they make than a scientist has about the cause of any experimental failure? At Transfyr, we are building the infrastructure to make real-world scientific work legible, transferable, and reproducible.

Modern science is capable of extraordinary outcomes, but much of the most important insights never become explicit: how experiments are actually executed, protocols drift, how experts make gametime decisions on the fly, why experiments fail on Tuesdays. This tacit knowledge is rarely captured, making it difficult to reliably reproduce results, much less hand off protocols to new team members or collaborators. We believe our systematic failure to capture tacit knowledge is holding back the entire industry.

We’re building systems that operate directly in real laboratory environments to elucidate, capture, and interpret this missing information. Our platform records and analyzes multimodal data about how scientific work is performed and turns it into durable, operational knowledge. In doing so, we are also building the world’s largest commercial dataset on real-world scientific execution.

This foundation is critical not only for driving elite human performance today, but for enabling meaningful automation tomorrow. Physical AI systems cannot learn from outcomes alone; they require rich, grounded records of how work is actually done in the real world.

Want to learn more? You can read some of our writings here.

About the Role

• We’re looking for a hands-on, Senior Scientist with expertise in virology and molecular biology workflows to conduct wet-lab experiments in our facility.

• You’ll be embedded in day-to-day lab operations to support the design and execution of experiments, uncover edge cases in protocols, and collaborate with AI, biology, and data engineers to help build the infrastructure behind fast, reproducible science.

• This is a true doer role in an early-stage startup. You will assist in the design and execution of reverse genetics-based plasmid virus production systems, assay development, troubleshooting and process optimization, and quality control.

What you’ll accomplish with us:

• Reverse Genetics: Design and implement reverse genetics systems for multiple virus families.

• Assay Design & Execution: Design, perform, and optimize molecular and virology assays including: plaque assays, reporter assays, nucleic acid extraction, PCR, RT-qPCR, cloning, gene manipulation, and sequencing to evaluate viral genomes.

• Troubleshoot laboratory protocols: support documentation, troubleshooting, and process improvements to enhance workflow reproducibility.

• Safety and Compliance: Uphold rigorous BSL-2 safety standards

Requirements:

• PhD, or MS with 3+ years of relevant experience, or BS with 5+ years of relevant experience in Virology, Molecular Biology, Computational Biology, Bioengineering Biology, or related field.

• Demonstrated hands-on lab experience (industry or academic) with the required wet lab techniques, including a track record of designing and using viral reverse genetics systems and plasmids.

• Exceptional experimental design with a strong bias toward documentation, reproducibility, and iteration.

• Ability to troubleshoot protocols systematically, with attention to both technical detail and human variability.

• Ability to clearly communicate technical concepts to cross-functional teams and collaborate on projects spanning AI, biology, and product.

• Located within commuting distance from Cambridge, MA.
  

Nice to Have

• Startup or early-stage experience preferred; comfort with ambiguity and rapid iteration is a must.

• Coding experience for complex data analysis and statistics (python, R, )

• Demonstrated experience using AI/ML tools for experimental design, data analysis, or predictive modeling.

• Direct customer-facing work in partner or external lab environments.