Machine Learning Scientist - Integrative Phenotyping - Remote

Overview

insitro's mission is to bring better drugs faster to the patients who can benefit most, through machine learning and data at scale. To address that goal, our discovery strategy integrates insights from multiple phenotypic readouts, spanning diverse high-content data modalities; we use data from public and proprietary human cohorts, and from in vitro cellular systems, generated by our proprietary, automated wet-lab platforms.

As a machine learning scientist on the integrative phenotyping team, you will develop, productionize, and deploy cutting-edge ML approaches to analyze and integrate large-scale multi-modal phenotypic datasets, including clinical imaging, electronic health records, physiological monitoring, longitudinal clinical data, biomarkers, and multi-omic modalities. You will work with clinical data from large human cohorts including national biobanks and other sources. You will contribute to developing models to understand patient state and predict outcomes and clinical endpoints. You will collaborate with a team of machine learning scientists, statistical geneticists, life scientists, and clinicians to identify therapeutic targets and develop drugs that have high efficacy and low toxicity. You will work in collaboration with software engineers to ensure these pipelines are robust, reusable components that can be deployed on large-scale datasets in a portable way. Your expertise will help the teams navigate the complexities of processing and cleaning high-quality data and ensure that the modeling strategies developed are performed to the highest rigor and in line with best practices in the field. You will report to the Director, Machine Learning, Integrative Phenotyping. We are open to both hybrid candidates local to the San Francisco Bay area and remote candidates for this role.

In Short

• Develop and deploy ML methods for interpreting complex phenotypes, and for integrating multi-modal analyses across diverse phenotypic readouts
• Provide technical leadership within a team of outstanding machine learning (ML) scientists
• Collaborate with other leaders in the company to achieve important goals
• Engineer robust, reusable platform components in partnership with the software engineering team

Requirements

• Expertise in developing and deploying state-of-the art ML methods for interpreting and extracting signals and clinically-relevant insights from complex data modalities
• 5+ years of experience with diverse clinical data modalities
• Experience with human physiology or disease biology
• Publication record of meaningful contributions in relevant ML, ML for health, computational biology, or biomedical venues
• Experience producing high-quality, reusable ML code
• Experience mentoring, coaching, and leading junior scientists

Benefits

• 401(k) plan with employer matching for contributions
• Excellent medical, dental, and vision coverage
• Open, flexible vacation policy
• Paid parental leave
• Quarterly budget for books and online courses for self-development
• Support to attend professional conferences
• New hire stipend for home office setup
• Monthly cell phone & internet stipend
• Access to free onsite baristas and cafe
• Access to free onsite fitness center