Lead/Senior Machine Learning Scientist (Integrative Phenotyping)

Location: South San Francisco, CA; in-person hybrid schedule of three days per week

Salary: $183,000–$224,000 starting salary for successful US-based applicants

Company

hirify.global is a physical AI drug discovery and development company using machine learning and large-scale multimodal biological and human cohort data to decode biology, identify therapeutic targets and biomarkers, and develop medicines.

What you will do

• Develop and deploy ML methods that extract precise phenotypes and biological insight from complex human cohort data, including MRI and functional genomics.
• Build models that characterize patient state and predict clinical outcomes from imaging, EHRs, longitudinal outcomes, biomarkers, and multi-omic readouts.
• Set rigorous modeling standards aligned with current best practices and build robust, reusable, tested platform components with software engineers.
• Integrate causal and multimodal evidence across phenotypic readouts to identify therapeutic targets.
• Partner with Therapeutic Area and Clinical Development colleagues on biomarkers for patient selection and clinical endpoints.
• Work with Statistical Genetics to connect human genetics with ML-derived phenotypes.

Requirements

• PhD in computer science, machine learning, or a related field, or 5+ years of equivalent applied ML research experience.
• Hands-on experience developing and deploying state-of-the-art ML methods, including multimodal techniques, to extract clinically relevant signals from complex data.
• Experience with several clinical data types, including clinical imaging such as MRI, DEXA, CT, or echocardiography; clinical records such as EHRs, medications, or outcomes; physiological recordings such as EEG or ECG; or biobank-scale human genetic data.
• Experience with high-content modalities such as single-cell or bulk omics, genetic perturbation screening, spatial proteomics, or pooled optical screening.
• Meaningful, high-quality publications or contributions in ML, ML for health, computational biology, or biomedical venues.
• Strong Python skills in a cloud environment and experience with modern deep learning frameworks, reusable tested ML code, and version control.
• Ability to deliver end-to-end ML work from sourcing and qualifying training data through model design, testing, and benchmarking.
• Ability to collaborate with ML scientists, statistical geneticists, life scientists, software engineers, and clinicians and make ML results legible to each group.

Nice to have

• Prior exposure to cardiovascular disease, neuroscience, or metabolism.

Culture & Benefits

• Full-time employment with annual performance bonus and equity incentive plan eligibility.
• 401(k) plan with employer matching, medical, dental, vision, mental health, and well-being support.
• Open vacation policy and paid parental leave of at least 16 weeks for birth parents and 10 weeks for other new parents.
• Quarterly budget for books and online courses, a home-office setup stipend, and monthly cell phone and internet stipends.
• Free onsite baristas, daily lunch for onsite or hybrid employees, and a commuter bus network serving the South San Francisco headquarters from across the Bay Area.
• Inclusive, growth-oriented culture with equitable treatment throughout the interview process.