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Senior Manager, Imaging Machine Learning

insitro· Data Science and Machine Learning
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South San Francisco, CA$247k - $262kFull-timePosted 4mo ago

About the role

Leadership role overseeing a team of machine learning researchers focused on extracting information from in-vitro biology using computer vision and ML, with collaboration across lab, imaging software, and computational biology to advance insitro's imaging platform and therapeutic programs.

Responsibilities

  • Lead, mentor, and grow a team of outstanding machine learning scientists to co-develop methods of extracting insights from in-vitro microscopy datasets
  • Work closely with laboratory leadership to structure assay development efforts, and empower members of your team to co-develop in-vitro microscopy assays suitable for genetic perturbation screening, often at whole-genome scale
  • Ensure the successful translation of assays you develop to insitro’s computational biology team, who will leverage the assays your teams develop to investigate causal biology through the integration of diverse data modalities, including microscopy
  • Co-develop the product vision for insitro’s industry-leading imaging software platform, and continue to support its development through method de-risking and translational development through adherence to established processes for contribution
  • Develop methods of measuring and qualifying microscopy data prior to model training and inference, including those which leverage agentic frameworks, VLMs, and self-supervised classification
  • Stay abreast of industrial trends and scientific literature in order to ensure insitro’s methods remain industry-leading and correctly matched to our applications.
  • Set yearly and quarterly strategic roadmaps for platform, set tactical goals for your team, and align with cross-functional stakeholders on a regular basis
  • Work shoulder-to-shoulder with your team where appropriate, participating in method/code review and authorship to model effective execution and cover gaps

Qualifications

  • Strong grounding in computer vision and machine learning fundamentals, with practical judgment about where these methods work and where they fail
  • Demonstrated experience applying CV/ML to pixel data to extract quantitative features and downstream biological insight
  • Working understanding of imaging principles — image formation, microscopy fundamentals, and the artifacts that arise from instruments and sample preparation
  • Hands-on experience with cellular imaging datasets (e.g. fluorescence/confocal or label-free microscopy)
  • 3+ years of people management, including solid-line management of multiple ICs and at least one senior (Staff-level) scientist or engineer
  • Track record of mentoring and growing technical talent day-to-day
  • Technical leadership as a decision-maker on projects, platforms, or teams
  • Strong communication and the ability to collaborate across functions, including with experimental and clinical life scientists

Skills

Required:Computer visionMachine learningImaging principles

Benefits

  • 401(k) plan with employer matching
  • 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
  • Quarterly budget for books and online courses for self-development
  • Support to attend professional conferences that are meaningful to your career growth and role's responsibilities
  • 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
Last updated Jul 23, 2026. Interested? Apply on the company site.

About insitro

Making Medicines Differently

At insitro, we are building a different kind of drug company to bring better drugs faster to the patients who can benefit most. Through the power of machine learning (ML) and data at scale, we decode the complexities of biology to unlock transformative new medicines.

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