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Infera seeks its first growth hire to shape how a lab software startup reaches scientists, from target labs to outreach and events personally. A strong candidate has several years in life science tools or lab software growth, knows how research labs buy and who decides, and can write and show up in person.
Building a repeatable playbook from scratch matters more than following an existing one. The role requires understanding AI-enabled lab workflows and the ability to explain that to skeptical
The first growth hire owns how a lab software startup reaches scientists, from picking target labs to running outreach and events personally. A strong candidate has several years in life science tools or lab software growth, knows how research labs buy and who decides, and can write and show up in person. Building a repeatable playbook from scratch matters more than following an existing one.
The product turns plain text lab protocols into instrument runs, so the growth work is explaining a new way of working to scientists who trust their own hands. AI helps draft content, build target lists and sort outreach results, but the judgment about which labs to pursue and the credibility in a room full of researchers stay human. Field conversations still shape what gets built next.
Working here means learning how AI tools fit into real lab workflows and how to explain that to skeptical researchers. A candidate can build this by using AI for outreach and content, and by understanding where protocol automation fits in academic and biotech labs. Bench or life science background helps translate the product for scientists.
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
Infera develops a natural language experimental compiler that converts plain text biological protocols into executable instrument runs.