About the role
About Anthrogen
Anthrogen is engineering post-modality biology. Today's modalities reflect historical contingencies in biological progress, not fundamental categories. We develop the AI systems that design modular biological machines and the experimental infrastructure to instantiate them. We're a small, high-density team in San Francisco building frontier AI and the biological systems to validate it, and we care most about people who move fast, go deep, and pick up whatever the problem needs.
The role
Our models can propose a new sequence quickly. Learning whether it works still depends on someone making the material correctly, running a careful experiment, and noticing when something is off. We want a research associate whose bench work we can trust and who wants to understand the science behind it.
You'll help build and characterize designed proteins, taking ownership of experimental workflows from construct preparation through sample quality control and assay execution. You'll work closely with Platform scientists, learn new methods, and improve the experiments you run. Following a protocol matters. Knowing when the protocol is no longer answering the question matters too.
What you'll do
- Execute molecular biology workflows, including cloning, PCR, transformations, and construct verification, with strong sample tracking and reproducibility.
- Express and purify proteins, assess material quality, and prepare samples for binding and functional experiments.
- Run established assays with appropriate controls and work with scientists to develop and troubleshoot new ones.
- Keep clear experimental records, perform initial data analysis, and flag unexpected results or quality problems early.
- Improve protocols and day-to-day lab workflows so that increased throughput does not come at the expense of trustworthy data.
Who you are
- You have excellent hands-on molecular biology or protein biochemistry skills, demonstrated through substantial bench work. A BS/MS in a relevant field or equivalent practical experience is a useful foundation.
- You can independently run a workflow you know, recognize common failure modes, and troubleshoot systematically rather than simply repeat it.
- You are careful with samples, controls, calculations, and records. You can explain how you know an experiment worked.
- You learn quickly, communicate clearly, and ask for help before an avoidable error becomes a week's worth of unusable work.
- You want responsibility for the quality of the science, not just completion of a task list.
Bonus points
- Mammalian cell culture, transfection, or cell-based assays.
- Experience with antibody production, protein characterization, or quantitative binding measurements.
- Lab automation, liquid handlers, or high-throughput workflows.
- Python or R for analyzing and organizing experimental data.
Logistics
Full-time, onsite in San Francisco.
Equity: 0.01-0.1%.