---
title: 'Lead/ Senior Machine Learning Scientist, Integrative Phenotyping at insitro'
canonical: 'https://feeny.ai/job/lead-senior-machine-learning-scientist-integrative-phenotyping-insitro-south-hscncem9jg0s'
type: 'job'
last_seen: '2026-11-03'
---

# Lead/ Senior Machine Learning Scientist, Integrative Phenotyping at insitro

- **Company:** insitro
- **Location:** South San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-11-02
- **Last confirmed live:** 2026-11-03
- **Apply:** https://jobs.ashbyhq.com/insitro/07f6a2ea-d889-4977-86ba-064637bdc155

## Job description

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, CT, echocardiography), clinical records (e.g., EHRs, medications, outcomes), physiological recordings (e.g., EEG, ECG), or biobank-scale human genetic data.
- Multimodal Experience: Experience with high-content modalities such as single-cell or bulk omics, genetic perturbation screening, spatial proteomics, or pooled optical screening.
- Publication Record: Meaningful, high-quality contributions in ML, ML for health, computational biology, or biomedical venues.
- Engineering Fluency: Strong Python in a cloud environment and modern deep learning frameworks, with a track record of reusable, tested, version-controlled ML code.

Core Competencies

- End-to-End Delivery: You work with other ML scientists and engineers to take a real-world problem from sourcing and qualifying training data through model design, testing, and benchmarking.
- Cross-Functional Translator: You collaborate well with statistical geneticists, life scientists, software engineers, and clinicians, and can make ML results legible to each.
- Biology-Curious: You want to understand the physiology behind the data, and prior exposure to cardiovascular disease, neuroscience, or metabolism is a plus.

## Compensation & Benefits at insitro

Our target starting salary for successful US-based applicants for this role is $183,000 - $224,000. 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. #LI-Onsite 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).

## About insitro

## Company Overview
- **One-liner**: insitro is a drug discovery company using machine learning, high-throughput biology, and human genetics to build causal models of disease and accelerate the development of transformative medicines.
- **Entity Type**: Private (Series C)
- **Headquarters**: South San Francisco, California, United States
- **Founded**: 2018
- **Founders**: Daphne Koller (CEO)

## Core Business
- **Primary industry**: Biotechnology Research; AI-driven drug discovery
- **Target customers**: B2B (pharma partnerships) and self-originated pipeline – therapeutic areas including metabolism (MASH, lipogenesis), oncology, and neuroscience
- **Mission/purpose**: “Bring better drugs faster to the patients who can benefit most” by decoding the complexities of biology with ML and data at scale

## Products & Services
- **Insitro Platform**: An industrialized ML platform that integrates in vitro cellular data (produced in automated labs) with human clinical and genetic data to identify causal disease drivers and design optimal therapeutic interventions.
- **Virtual Human™**: A genetically anchored causal AI engine that models how disease begins, progresses, and can be resolved.
- **TherML™ AI Platform**: An AI system for designing optimal small molecule medicines.
- **Pipeline Programs**: Wholly-owned and partnered programs in metabolism (e.g., CTRO-1013 for MASH), oncology (ADC biology), and neuroscience.

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metric – Total Funding**: $743M (per LinkedIn) to >$750M (per company press release); includes Series A ($100M, 2018; $100M, 2019), Series B ($143M, 2020), Series C ($400M, 2021)
- **Annual Revenue**: $20.3M (LinkedIn estimate; also reported ~$140M in total collaboration revenue to date from partnerships with BMS, Lilly, and Gilead)
- **Notable Investors/Partners**: a16z, ARCH, BlackRock, Casdin, CPP Investments, Foresite Capital, GV, SoftBank, Temasek, Third Rock Ventures, T. Rowe Price. Partners include Bristol Myers Squibb, Eli Lilly, Gilead.
- **Growth Signals**: Headcount decreased ~20.6% YoY to ~211 employees; however active job postings increased 400% YoY (10 postings). The lead MASH candidate CTRO-1013 is expected to enter first-in-human clinical trials in 2026. New data presented at ADA 2025 shows anti-fibrotic signals.

## Competitive Advantages
- **Causal biology focus**: Integrates human genetics, multi-modal cellular data, and clinical imaging to identify causal intervention points – distinguishes from purely correlative AI models.
- **Industrialized learning loop**: Each program generates data that improves the platform’s predictive models, enabling faster scaling across therapeutic areas.
- **World-class team and investors**: Led by AI pioneer Daphne Koller with backing from top-tier tech and healthcare investors.
- **Revenue‑generating partnerships**: Validated by large pharma collaborations (BMS, Lilly, Gilead) bringing in ~$140M.

## Strategic Focus
- **Advancing pipeline to clinic**: CTRO-1013 (IRS1 inhibitor for MASH) is the lead wholly-owned program entering human trials in 2026. Additional programs in metabolism, oncology, and neuroscience are progressing.
- **Deepening platform capabilities**: Continued investment in automation, multi-modal data generation (imaging, genomics, proteomics), and ML model refinement across all biology scales.
- **Expanding partnerships**: Leveraging platform to support partner drug discovery while retaining wholly-owned programs.

## Why Work Here
- **Culture**: Cross-disciplinary environment where life scientists, data scientists, engineers, and drug hunters collaborate on first-in-class drug discovery problems.
- **Work model**: Roles primarily based in South San Francisco, CA and Krakow, Poland; specific remote/hybrid policy not publicly detailed.
- **Notable perks**: Not explicitly listed, but the company emphasizes a “unique culture” focused on scientific breakthroughs and scaling data-driven medicine.
- **Employer ratings**: Mixed (2.7/5 on LinkedIn from 31 reviews). Compensation scores higher (3.6/5) while culture (2.6/5) and career development (2.7/5) are areas of concern.
- **Engineering/ML culture**: Strong focus on applying state-of-the-art ML (including generative AI, causal inference, imaging analysis) to real biological problems. Open roles span ML science, software engineering (scientific pipelines), and computational biology.
- **Growth trajectory**: Despite recent headcount reductions, the near-term clinical milestone (CTRO-1013 Phase 1) and increased hiring point to a potential inflection point.

## Sources
1. [insitro.com – Company site](https://www.insitro.com/)
2. [insitro.com – Platform page](https://www.insitro.com/platform/)
3. [LinkedIn – Insitro company page](https://www.linkedin.com/company/insitro)
4. [CBInsights – Insitro company profile](https://www.cbinsights.com/company/insitro)
5. [Greenhouse – Insitro careers page](https://boards.greenhouse.io/insitro)

## Other roles at insitro

- [Vice President, FP&A & Financial Transformation](https://feeny.ai/job/vice-president-fp-a-financial-transformation-insitro-south-san-francisco-cdp49byy462j) — South San Francisco, CA
- [Vice President, Regulatory Affairs](https://feeny.ai/job/vice-president-regulatory-affairs-insitro-south-san-francisco-ap5d1em1hqjk) — South San Francisco, CA
- [Director, Financial Reporting & Technical Accounting](https://feeny.ai/job/director-financial-reporting-technical-accounting-insitro-south-san-francisco-gynm79dbmdwn) — South San Francisco, CA
- [Full Stack Software Engineer, Lab Platform (LIMS)](https://feeny.ai/job/full-stack-software-engineer-lab-platform-lims-insitro-south-san-francisco-q1n6e6kjbmsx) — South San Francisco, CA
- [Senior Manager / Director, Statistical Genetics](https://feeny.ai/job/senior-manager-director-statistical-genetics-insitro-south-san-francisco-f30j4ng5z3q5) — South San Francisco, CA
- [Associate Scientist III, Cardiac Modeling](https://feeny.ai/job/associate-scientist-iii-cardiac-modeling-insitro-south-san-francisco-xfsc4xtkj93z) — South San Francisco, CA
- [Senior Director, Quality Assurance](https://feeny.ai/job/senior-director-quality-assurance-insitro-south-san-francisco-9enwbdgv2t0y) — South San Francisco, CA
- [Senior Data Scientist, CompBio](https://feeny.ai/job/senior-data-scientist-compbio-insitro-south-san-francisco-324575g11esn) — South San Francisco, CA
- [Senior/ Staff Software Engineer, Imaging](https://feeny.ai/job/senior-staff-software-engineer-imaging-insitro-south-san-francisco-50jmxgaczv65) — South San Francisco, CA
- [Counsel / Associate Director, Sr. Counsel](https://feeny.ai/job/counsel-associate-director-sr-counsel-insitro-south-san-francisco-rtew4z5mnxnp) — South San Francisco, CA