Lead/ Senior Machine Learning Scientist, Integrative Phenotyping

The posting, as insitro wrote it

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 Lead/ Senior Machine Learning Scientist on the Integrative Phenotyping team, you will develop, productionize, and deploy cutting-edge ML approaches to build precise phenotypes from large-scale multimodal datasets — clinical imaging, electronic health records, longitudinal outcomes, biomarkers, and multi-omic readouts — and use them to understand patient state, predict clinical endpoints, and identify therapeutic targets.

You’ll work alongside machine learning scientists, statistical geneticists, life scientists, software engineers, and clinicians, and your expertise will shape how the company builds rigorous ML on complex human data.

Based in South San Francisco, this position reports directly to the Head of Integrative Phenotyping and offers an in-person hybrid schedule of three days per week.

RESPONSIBILITIES

ML Methods & Platform

• Build Precise Phenotypes: Develop and deploy ML methods that extract biological insight from complex, high-dimensional human cohort data such as MRI and functional genomics.
• Model Patient State: Develop models that characterize patient state and predict outcomes and clinical endpoints from multimodal data including clinical imaging, EHRs, longitudinal outcomes, biomarkers, and multi-omic readouts.
• Set the Bar: Ensure modeling strategies are rigorous, effective, and aligned with best practices in the field.
• Engineer Reusable Components: Build robust, reusable platform components in partnership with the software engineering team.

Target Discovery & Translation

• Integrate Causal Evidence: Combine causal, multimodal analyses across diverse phenotypic readouts to select better therapeutic targets.
• Biomarkers & Endpoints: Partner with Therapeutic Area and Clinical Development colleagues to develop new biomarkers for patient selection and clinical endpoints.
• Connect Genetics to Phenotypes: Work with the Statistical Genetics team to associate human genetics with ML-derived phenotypes.

ABOUT YOU

Experience & Qualifications

• Proven Tenure: PhD in computer science, machine learning, or a related field, or 5+ years of equivalent applied ML research experience.
• Modern ML Expertise: Hands-on experience developing and deploying state-of-the-art ML methods, including multimodal techniques, to extract clinically relevant signals from complex data.
• Clinical Data Depth: Experience with several of: clinical imaging (e.g., MRI, DEXA,

[…]
rovides 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.

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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.

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.