T
Not Specified Permanent

New York City, New York · USA job

Staff AI Scientist - AI Products / Life Sciences

Tempus

New York City, New York

Job description

Overview

As a Staff AI Scientist at Tempus, you will lead the design and deployment of multimodal AI models that fuse clinical and molecular data to improve patient care. You will shape research-to-production work on a large-scale healthcare dataset, collaborating with cross-functional teams to advance precision medicine. Your work will influence biomarkers, therapy outcomes, and Companion Diagnostics within a regulatory-compliant framework. This role offers high-impact research with real-world clinical impact.

Compensation / Benefits
  • incentive compensation
  • restricted stock units (RSUs)
  • medical benefits
  • remote work options
  • competitive salary range
  • career development opportunities
Responsibilities
  • Architect and lead AI-intensive projects from research to production-ready design, shaping the technical roadmap
  • Design and train multimodal models using data such as pathology slides, genomic profiles, spatial omics, and longitudinal records
  • Develop AI solutions to support biomarker discovery, therapy outcome prediction, and Companion Diagnostics (CDx)
  • Ensure AI products meet regulatory guidelines and quality standards in healthcare applications
  • Publish original research and engage with the global AI community
  • Collaborate with Life Sciences companies to advance biomarker and CDx initiatives
Key requirements
  • 5+ years of industry experience leading end-to-end ML model development from research to deployment
  • Expertise in large-scale deep learning and production-grade models
  • Experience in computer vision and multimodal modeling (pathology, multi-omics)
  • Strong track record of peer-reviewed publications; medical AI publications preferred
  • Proficiency in Python and deep learning stack (e.g., PyTorch) and solid software engineering practices
  • leadership and direction for high-impact projects
  • collaboration across cross-functional teams
  • clear scientific communication and public dissemination
  • multimodal modeling
  • pathology image analysis (WSI)
  • omics data integration (DNA/RNA)

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