Full Stack Software Engineer - Scientific Pipelines

The heart of insitro’s strategy is the combination of novel, cutting edge methods in machine learning, biology at scale and small molecule discovery that address key bottlenecks in the drug development pipeline.  This strategy requires a seamless, robust, and effective operation that simultaneously spans multiple projects, some partnered and some in-house. Our success relies on working across functions, including external research partners, to ensure that projects have what they need for successful execution.

Central to insitro's thesis is our ability to integrate rich datasets across modalities. From live cell imaging to single-cell RNA sequencing to DNA encoded libraries, insitro generates a diverse and ever growing torrent of data. Our team, Scientific Pipelines, develops the foundation of data pipelines that transform that torrent into the actionable datasets driving our target and drug discovery efforts.

In this role, you will democratize access to our data through tools that enable exploration and empower our scientists to design their next experiments, creating tight feedback loops back to the lab. To achieve this, you’ll partner directly with scientists and engineers to design and build a cohesive suite of data explorers that integrate seamlessly with our LIMS and data pipelining systems.

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

Examples of projects you will be working on:

• Build an interconnected suite of target exploration tools that allow scientists to triage gene targets across our therapeutic areas based on the data we generate and ingest
• Expose our microscopy images and machine learning derived features to both wet- and dry-lab scientists
• Design intuitive workflows that allow scientists to navigate from the experiments they have designed and run to the downstream datasets and features we produced

• Placing a high degree of trust in your ideas and execution
• Bringing you up to speed in the domain of drug development
• Strive to provide 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

• You have 5+ years of experience as a professional software engineer with 3+ years of front end experience
• You’re eager to ship work that makes a difference to scientists and ultimately patients
• 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/Azure), relational databases, writing design docs, version control, doing code reviews, perfecting our slackmoji game
• Bonus
• Experience with biological data visualization (such as sequencing or microscopy) for medium sized datasets (100TB+)
• Experience with our stack: AWS, FastAPI, SQLAlchemy, React, TypeScript, streamlit, PostgreSQL, Docker

Our target starting salary for successful US-based applicants for this role is $150,000 - $200,000. To determine starting pay, we consider multiple job-related factors including a candidate’s skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.

This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.