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South San Francisco, California, United States
Hybrid
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 & 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
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
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, and if in doubt, contact us at info@insitro.com.
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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.