The Opportunity

At insitro we are trying to greatly increase the success rate of drug development by combining human biology and machine learning, at scale.

To enable that mission we need a software layer that ties together the scientific, automation, and machine learning platforms: that software is our Lab Platform!

We’re a team of ~7 engineers with a mission to accelerate the pace of science at insitro. 

Projects on our roadmap include productionizing our new state-of-the-art Pooled Optical Screen assay, building out our next-gen experimental design tool, and delivering the v0 of our end-to-end LIMS stack. These projects push forward some really cool solutions in robotics, workflow automation, and lab orchestration technology.

What you’ll do:

• Ship stuff that makes our scientists say “OMG, this is amazing, thank you so much!”
• Collaborate cross functionally with folks from our ML, automation, and biology groups
• Understand our mission and contribute to our roadmap with your own ideas
• Shape our early-ish engineering culture with your ideas
• All the normal SWE stuff: write code, review design docs, talk to users, and do code reviews.
• Ultimately you’ll move the needle in a meaningful way for insitro and field of medicine

In return, we will support you by:

• Placing a high degree of trust in your ideas and execution.
• Bringing you up to speed in the domain of drug development
• Providing a low-stress work environment.
• Making ourselves available for collaboration.
• Caring about you as a whole person— not a resource
• Being a well funded startup with conservative runway

About you:

• You have 4-6+ years of experience as a professional software engineer
• You’re eager to ship stuff that makes a difference to users
• You feel comfortable reasoning about the tradeoffs between quality and speed when building in a startup environment
• You’re familiar with the usual SWE things: AWS (or GCP), relational databases, writing design docs, version control, doing code reviews, goofing around on slack.
• Bonus:
  • Experience with LIMS, large datasets, automation, or a life sciences domain
  • Experience with our stack: Django, Flask, FastAPI, SQLAlchemy, React, TypeScript, PostgreSQL, Docker