Insitro

HQ
San Francisco
Total Offices: 2
173 Total Employees
Year Founded: 2018

Jobs at Insitro

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Recently posted jobs

YesterdaySaved
Hybrid
South San Francisco, CA, USA
Healthtech • Machine Learning • Biotech
Lead and build insitro’s FP&A function, owning company-wide planning, rolling forecasts, scenario analysis, headcount modeling, finance systems, and AI-enabled reporting. Partner with Accounting, Research, Clinical Development, People, Investor Relations, and Corporate Development. Lead the FP&A team, present financial materials to the Executive Team, Board, and Audit Committee, support IPO readiness, and ensure consistent planning, guidance, and capital allocation narratives.
7 Days AgoSaved
Hybrid
South San Francisco, CA, USA
Healthtech • Machine Learning • Biotech
Own financial reporting, annual audits, US GAAP technical accounting, complex transactions, accounting policies, stock compensation, tax coordination, international compliance, and internal controls. Partner with auditors, legal, corporate development, finance, and executives while supporting biotech pipeline accounting. Build scalable reporting workflows using AI tools and prepare the organization for SOX compliance, SEC reporting, and eventual public-company readiness.
One Month AgoSaved
Hybrid
South San Francisco, CA, USA
Healthtech • Machine Learning • Biotech
Build and own full-stack software for insitro’s laboratory platform, including React and TypeScript interfaces, Python services, database models, instrument and Benchling integrations, and agent runtimes. Partner with scientists, biology, automation, and machine learning teams to understand workflows and deliver useful, verifiable tools. Prototype agentic tooling, support production reliability, review code and designs, and contribute to accelerating drug development.
One Month AgoSaved
Hybrid
South San Francisco, CA, USA
Healthtech • Machine Learning • Biotech
Build and lead imaging software infrastructure spanning microscope acquisition, image processing, high-throughput ML pipelines, data visualization, quality control, and laboratory automation. Scale research prototypes into reliable systems processing millions of images daily while ensuring data integrity, lineage, reproducibility, and observability. Partner with laboratory, ML, and microscopy scientists to translate research needs into production software, own architectural decisions, document systems, and mentor engineers.
2 Months AgoSaved
Hybrid
South San Francisco, CA, USA
Healthtech • Machine Learning • Biotech
Counsel or Senior Counsel will draft and negotiate high-volume commercial, technology, research, vendor, supplier, and employment-related agreements. The role partners with R&D, lab, IT, procurement, finance, HR, CMC, and technical teams on MTAs, CRO/CDMO agreements, cloud and compute contracts, and AI/ML matters. Responsibilities also include improving templates, playbooks, approval workflows, CLM tools, and AI-enabled legal processes while providing practical business advice.
2 Months AgoSaved
Hybrid
South San Francisco, CA, USA
Healthtech • Machine Learning • Biotech
Develop and deploy computer-vision and ML pipelines for microscopy datasets, partner with biologists and engineers, benchmark and calibrate tools, extract disease-relevant phenotypes, and communicate results to cross-functional stakeholders.
2 Months AgoSaved
Hybrid
South San Francisco, CA, USA
Healthtech • Machine Learning • Biotech
The Senior Director of Project & Portfolio Management will lead cross-functional teams, develop integrated project plans, and establish AI-forward project management methodologies to advance drug candidates in a hybrid work environment.
2 Months AgoSaved
In-Office
South San Francisco, CA, USA
Healthtech • Machine Learning • Biotech
Lead and grow a team of machine learning scientists to develop computer-vision methods for in‑vitro microscopy. Partner with lab and imaging software teams to co-develop assays, translate methods to computational biology, set roadmaps, participate in code and method reviews, and advance imaging QC and self-supervised/VLM-based approaches to drive therapeutic programs.