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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer, Imaging - **Company:** insitro - **Location:** South San Francisco, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $219,000.0 - $233,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Data Analysis, Computer Vision, Data Integrity, Distributed Systems, Experimental Data, Graphics Software, Python (Programming Language), Machine Learning, Azure Machine Learning, Scientific Computating, Pytorch, Kubernetes, Data Lineage, Machine Learning Operations, Data Pipelines - **Published:** August 25, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=6945a7157fffefda ## About the Role * Proven Tenure: 8+ years of professional experience building and operating production-grade software and high-throughput data pipelines, primarily in Python * ML Platform Depth: You have designed, built, and deployed scientific computing pipelines, visualizations, and QC processes for large-scale imaging or similarly high-dimensional datasets * Distributed Systems Stack: Hands-on experience with a Python-first ML stack, distributed compute (e.g., PyTorch/Lightning, Ray, Kubernetes), and workflow orchestration (e.g., Argo, Airflow, or redun) * End-to-End Delivery: A track record of owning complex systems from architecture through production operation Core Competencies * Cross-Functional Partnership: You thrive alongside scientists and excel at translating abstract research needs into practical, scalable software * Mission-Driven: You're motivated by enabling scientific breakthroughs through robust platform engineering * Force Multiplier: You enjoy mentoring and leveling up the engineers around you ## Description 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. Responsibilities Platform & Tooling * 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 * Production Hardening: Scale and harden complex image processing and ML workflows, taking them from research prototypes to systems that reliably process millions of images per day * Data Integrity: Set and uphold best-in-class practices for data integrity, lineage tracking, reproducibility, and observability across the entire imaging data lifecycle * Documentation: Write clear, exemplary technical specifications and documentation that others build on Cross-Functional Partnership * Scientific Translation: Work closely with lab scientists, ML scientists, and microscopy teams to translate complex experimental needs into clear, actionable technical plans and shipped software * Mentorship: Raise the technical bar across the team by sharing knowledge and mentoring other engineers ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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