---
title: 'Staff Software Engineer, Imaging at insitro'
canonical: 'https://feeny.ai/job/staff-software-engineer-imaging-insitro-south-san-francisco-50jmxgaczv65'
type: 'job'
last_seen: '2026-09-08'
---

# Staff Software Engineer, Imaging at insitro

- **Company:** insitro
- **Location:** South San Francisco, CA
- **Employment:** full-time
- **Posted:** 2026-08-25
- **Last confirmed live:** 2026-09-08
- **Apply:** https://jobs.ashbyhq.com/insitro/ff6605ae-4961-4a06-b656-6d7dc665d990

## Job description

## 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—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

## ABOUT YOU

## Experience & Qualifications

- 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

## COMPENSATION & BENEFITS AT INSITRO

Our target starting salary for successful US-based applicants for this role is $219,000 - $233,000. 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.

In addition, insitro also provides our employees:

- 401(k) plan with employer matching for contributions
- Excellent medical, dental, and vision coverage as well as mental health and well-being support
- Open, flexible vacation policy
- Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)
- Quarterly budget for books and online courses for self-development
- New hire stipend for home office setup
- Monthly cell phone & internet stipend
- Access to free onsite baristas and daily lunch for employees who are either onsite or hybrid
- Access to a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area

insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process.

Please be aware of recruitment scams: we never request payments, all recruitment communications are from @insitro.com http://insitro.com, and if in doubt, contact us at info@insitro.com.

#LI-Hybrid

## About insitro

insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro’s approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com http://www.insitro.com.

## About insitro

## Company Overview
- **One-liner**: insitro is a drug discovery company using machine learning, high-throughput biology, and human genetics to build causal models of disease and accelerate the development of transformative medicines.
- **Entity Type**: Private (Series C)
- **Headquarters**: South San Francisco, California, United States
- **Founded**: 2018
- **Founders**: Daphne Koller (CEO)

## Core Business
- **Primary industry**: Biotechnology Research; AI-driven drug discovery
- **Target customers**: B2B (pharma partnerships) and self-originated pipeline – therapeutic areas including metabolism (MASH, lipogenesis), oncology, and neuroscience
- **Mission/purpose**: “Bring better drugs faster to the patients who can benefit most” by decoding the complexities of biology with ML and data at scale

## Products & Services
- **Insitro Platform**: An industrialized ML platform that integrates in vitro cellular data (produced in automated labs) with human clinical and genetic data to identify causal disease drivers and design optimal therapeutic interventions.
- **Virtual Human™**: A genetically anchored causal AI engine that models how disease begins, progresses, and can be resolved.
- **TherML™ AI Platform**: An AI system for designing optimal small molecule medicines.
- **Pipeline Programs**: Wholly-owned and partnered programs in metabolism (e.g., CTRO-1013 for MASH), oncology (ADC biology), and neuroscience.

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metric – Total Funding**: $743M (per LinkedIn) to >$750M (per company press release); includes Series A ($100M, 2018; $100M, 2019), Series B ($143M, 2020), Series C ($400M, 2021)
- **Annual Revenue**: $20.3M (LinkedIn estimate; also reported ~$140M in total collaboration revenue to date from partnerships with BMS, Lilly, and Gilead)
- **Notable Investors/Partners**: a16z, ARCH, BlackRock, Casdin, CPP Investments, Foresite Capital, GV, SoftBank, Temasek, Third Rock Ventures, T. Rowe Price. Partners include Bristol Myers Squibb, Eli Lilly, Gilead.
- **Growth Signals**: Headcount decreased ~20.6% YoY to ~211 employees; however active job postings increased 400% YoY (10 postings). The lead MASH candidate CTRO-1013 is expected to enter first-in-human clinical trials in 2026. New data presented at ADA 2025 shows anti-fibrotic signals.

## Competitive Advantages
- **Causal biology focus**: Integrates human genetics, multi-modal cellular data, and clinical imaging to identify causal intervention points – distinguishes from purely correlative AI models.
- **Industrialized learning loop**: Each program generates data that improves the platform’s predictive models, enabling faster scaling across therapeutic areas.
- **World-class team and investors**: Led by AI pioneer Daphne Koller with backing from top-tier tech and healthcare investors.
- **Revenue‑generating partnerships**: Validated by large pharma collaborations (BMS, Lilly, Gilead) bringing in ~$140M.

## Strategic Focus
- **Advancing pipeline to clinic**: CTRO-1013 (IRS1 inhibitor for MASH) is the lead wholly-owned program entering human trials in 2026. Additional programs in metabolism, oncology, and neuroscience are progressing.
- **Deepening platform capabilities**: Continued investment in automation, multi-modal data generation (imaging, genomics, proteomics), and ML model refinement across all biology scales.
- **Expanding partnerships**: Leveraging platform to support partner drug discovery while retaining wholly-owned programs.

## Why Work Here
- **Culture**: Cross-disciplinary environment where life scientists, data scientists, engineers, and drug hunters collaborate on first-in-class drug discovery problems.
- **Work model**: Roles primarily based in South San Francisco, CA and Krakow, Poland; specific remote/hybrid policy not publicly detailed.
- **Notable perks**: Not explicitly listed, but the company emphasizes a “unique culture” focused on scientific breakthroughs and scaling data-driven medicine.
- **Employer ratings**: Mixed (2.7/5 on LinkedIn from 31 reviews). Compensation scores higher (3.6/5) while culture (2.6/5) and career development (2.7/5) are areas of concern.
- **Engineering/ML culture**: Strong focus on applying state-of-the-art ML (including generative AI, causal inference, imaging analysis) to real biological problems. Open roles span ML science, software engineering (scientific pipelines), and computational biology.
- **Growth trajectory**: Despite recent headcount reductions, the near-term clinical milestone (CTRO-1013 Phase 1) and increased hiring point to a potential inflection point.

## Sources
1. [insitro.com – Company site](https://www.insitro.com/)
2. [insitro.com – Platform page](https://www.insitro.com/platform/)
3. [LinkedIn – Insitro company page](https://www.linkedin.com/company/insitro)
4. [CBInsights – Insitro company profile](https://www.cbinsights.com/company/insitro)
5. [Greenhouse – Insitro careers page](https://boards.greenhouse.io/insitro)

## Other roles at insitro

- [Senior Director, Quality Assurance](https://feeny.ai/job/senior-director-quality-assurance-insitro-south-san-francisco-9enwbdgv2t0y) — South San Francisco, CA
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- [Counsel / Senior Counsel](https://feeny.ai/job/counsel-senior-counsel-insitro-south-san-francisco-rtew4z5mnxnp) — South San Francisco, CA
- [Vice President, Regulatory Affairs](https://feeny.ai/job/vice-president-regulatory-affairs-insitro-south-san-francisco-ap5d1em1hqjk) — South San Francisco, CA
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- [Senior Manager / Associate Director, Project & Portfolio Management](https://feeny.ai/job/senior-manager-associate-director-project-portfolio-management-insitro-south-jrx049q0j47k) — South San Francisco, CA
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