← Insitro

Senior/ Staff Software Engineer, Imaging

Onsite: US   South San Francisco, CA

Why we labeled it Onsite
Location field: "South San Francisco, CA" (not marked remote)
Salary: $191,000 - $233,000
Skills: Python, PyTorch, Kubernetes, Agents, Data pipelines

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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 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 the platform features that make novel in vitro screening modalities and ML-derived phenotypes integral to our discovery workflows, partnering with lab scientists, ML scientists, and our automation teams to turn research prototypes into validated screening workflows that reliably process terabytes of biological data per day. This is a chance to set the technical direction for how imaging, automation, machine learning, and agentic analysis 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. Scalability & Data Integrity Scalability: Scale and harden complex ML workflows, taking them 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 entire 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 Senior/ Staff experience: 6+ years of professional experience building and operating production-grade software and high-throughput data pipelines, primarily in Python. ML Platform Depth (highly valued): You have designed, built, and maintained scientific computing pipelines, visualizations, and QC processes for large-scale biological datasets. 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. Core Competencies Cross-Functional Partnership: You thrive alongside scientists and excel at translating abstract research needs into practical, reliable, and 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 $191,000 - $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