Lead ML Scientist, Integrative Phenotyping (Multimodal)

Warmada; South San Francisco (CA); Hybrid; USD 183,000 - 224,000; Full time

Benefits offered by this job

401(k) plan with employer matching

Excellent medical/dental/vision

Paid parental leave

Home office stipend

Monthly cell phone & internet stipend

Job summary

insitro is seeking a Lead/Senior Machine Learning Scientist for the Integrative Phenotyping team in South San Francisco. You will develop, productionize, and deploy ML methods to build precise phenotypes from multimodal data including MRI, EHRs, and biomarkers, to understand patient state and predict clinical endpoints.

You will collaborate across ML, genetics, biology, and clinical teams. You will work in an in-person hybrid schedule with direct reporting to the Head of Integrative Phenotyping.

Qualifications

• PhD or 5+ years of applied ML research experience.
• Experience with multimodal data (imaging, EHR, biomarkers) preferred.
• Strong Python and cloud-based ML deployment experience.

Responsibilities

• Build, productionize, and deploy ML methods to extract phenotypes from large-scale multimodal data.
• Model patient state and predict outcomes from diverse data sources.
• Ensure rigor and best practices in modeling approaches.
• Engineer reusable platform components with software engineering partners.
• Integrate causal analyses to identify therapeutic targets.
• Develop biomarkers and endpoints for patient selection and trial design.
• Collaborate with genetics, biology, and clinical teams to translate ML insights.

Skills

PhD in ML/CS

Multimodal ML

Python

Cloud ML frameworks

Research to production

End-to-end delivery

Education

PhD in computer science, ML, or related field

Tools

Python

Cloud environments

Deep learning frameworks

Job description

insitro is seeking a Lead/Senior Machine Learning Scientist for the Integrative Phenotyping team in South San Francisco. You will develop, productionize, and deploy ML methods to build precise phenotypes from multimodal data including MRI, EHRs, and biomarkers, to understand patient state and predict clinical endpoints.

You will collaborate across ML, genetics, biology, and clinical teams. You will work in an in-person hybrid schedule with direct reporting to the Head of Integrative Phenotyping.