Senior/ Staff Software Engineer, Imaging

The Opportunity

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.

As a Senior/Staff Software Engineer on our Imaging Software team, you will define and expand our data and ML infrastructure across the full data lifecycle — from data generation, high-throughput ML pipelines, to analysis results. You'll build platform features that make novel in vitro screening modalities and ML-derived phenotypes integral to discovery workflows, partnering with lab scientists, ML scientists, and automation teams to turn research prototypes into validated screening workflows that process terabytes of biological data per day.

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

Responsibilities

Platform & Tooling

• Platform Enablement: Partner with lab and ML scientists to design, develop, and scale 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.
• Architectural Ownership: Own complex, end-to-end projects, making thoughtful architectural trade-offs with long-term maintainability in mind.

Scalability & Data Integrity

• Scalability: Scale and harden complex ML workflows from research prototypes to systems that reliably process terabytes of data per day.
• Data Integrity: Set and uphold best-in-class practices for data integrity, lineage tracking, reproducibility, and observability across the data lifecycle.
• Documentation: Write clear technical specifications and documentation.

Cross-Functional Partnership

• Scientific Translation: Work closely with lab scientists, ML scientists, and microscopy teams to translate complex experimental needs into actionable technical plans and shipped software.
• Mentorship: Raise the technical bar across the team by sharing knowledge and mentoring other engineers.

Qualifications

• Experience: 6+ years of professional experience building and operating production-grade software and high-throughput data pipelines, primarily in Python.
• ML Platform Depth: Experience designing, building, and maintaining scientific computing pipelines, visualizations, and QC processes for large-scale biological datasets (highly valued).
• Core Stack: Hands-on experience with a Python-first ML stack (PyTorch/Lightning), distributed compute (Ray, Dask, Kubernetes, etc.), and workflow orchestration (Argo, Airflow, redun, etc.), deployed on cloud infrastructure at multi-terabyte scale.
• End-to-End Delivery: A track record of owning complex systems from architecture through production operation.