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Job Opening

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Staff Software Engineer, Imaging

Insitro · South San Francisco, CA · Posted 72 days ago

$219k–$233khybridic
8+ yrs expPythonMachine LearningComputer VisionKubernetesPyTorchRayAirflowArgo

insitro is a physical AI company dedicated to unlocking causal human biology and accelerating the delivery of better medicines to patients. Our unique Virtual Human™ platform identifies novel, high-impact genetic intervention points, which our TherML™ platform translates into therapeutics—whether small molecules, biologics, or oligos. With multiple programs in metabolic disease and neuroscience advancing toward the clinic, and our first IND submission slated for the second half of this year, we are at a pivotal inflection point.

As a Staff Software Engineer on our Imaging Software team, you will define and expand our computer vision and ML infrastructure across the full imaging data lifecycle — from on-microscope acquisition to high-throughput ML pipelines. You'll build the platform features that make novel imaging modalities and ML-derived phenotypes integral to our discovery workflows, partnering daily with lab scientists, ML scientists, and our microscopy team to turn research prototypes into validated screening workflows that run reliably at laboratory automation scale. This is a chance to set the technical direction for how imaging, automation, and machine learning converge in drug discovery.

Based in South San Francisco, this position reports directly to the Director of Imaging, Cellular Machine Learning and offers an in-person hybrid schedule of three days per week.

  • Platform Enablement: Partner with lab and ML scientists to design, develop, and scale the platform capabilities needed to run and interpret ML-powered high-content imaging screens
  • User Tooling: Build and evolve robust tools and interactive interfaces for data exploration, quality assessment, and visualization so scientists can iterate quickly on experimental data
  • Architectural Ownership: Own complex, end-to-end projects, making thoughtful architectural trade-offs, and delivering incrementally with long-term maintainability in mind

Production Hardening & Data Integrity

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