Tempus AI

Lead the scientific development of agentic AI frameworks for discovering prognostic and predictive models in oncology, integrating LLM orchestration with translational science. Architect 'deep agents' for hypothesis generation, experimental design, and multimodal ML using foundation models. Innovate scientific methodology, develop predictive models and causal inference frameworks, and scale scientific discovery.

This role is for a GenAI Product Builder in the healthcare domain, focusing on leveraging AI and agentic tools to simplify product development and deliver customer solutions. The role involves end-to-end product ownership, designing and prototyping experiences, developing and engineering solutions using AI tools, and championing standards for scale. It is targeted at recent graduates with a strong aptitude for problem-solving, technical know-how, and process engineering.

Staff AI Scientist role focused on researching, designing, and deploying multimodal AI models for precision medicine and therapeutic solutions in healthcare, leveraging large clinical and molecular datasets. The role involves technical leadership, algorithmic innovation, collaboration with life sciences companies, ensuring regulatory alignment, and scientific contribution through publications. Requires a Ph.D., 5+ years of industry experience in end-to-end ML model development, and expertise in deep learning, computer vision, and multimodal modeling.

Staff Machine Learning Engineer focused on architecting, building, and maintaining the critical data infrastructure for large multimodal generative AI models in healthcare, processing diverse data types like genomics, pathology images, and clinical notes.

Director of Epidemiology & Methodological Innovation to lead high-impact research for biopharma partners, focusing on developing and validating novel epidemiological methods using multimodal datasets (clinical, molecular/genomic) and applying causal inference and machine learning techniques. This role involves client-facing strategy, scientific thought leadership, and bridging data science with productization, with a strong emphasis on regulatory-grade insights for drug development.

This role focuses on building specialized AI agents and workflows that leverage LLMs to help clients derive insights from large-scale biomedical data. It involves client onboarding, scientific problem-solving, platform guidance, and creating AI-assisted tools for data analysis. The role requires experience in data science, machine learning, Python/R, and putting data science workflows into production, with a strong emphasis on using AI-assisted development tools.

Associate Director RWE, PharmaR&D at Tempus AI, focusing on designing and executing research projects for biopharmaceutical partners using real-world evidence and AI. The role involves computational analysis, guiding algorithm development, and incorporating LLMs and agentic workflows into research processes to advance cancer precision medicine.

This internship focuses on applying data science and machine learning techniques, specifically Large Language Models (LLMs), to streamline business operations through automation for document processing and data extraction, aiming to modernize business workflows and improve operational efficiency.

Seeking an AI Data Science Summer Associate to apply advanced AI/ML techniques, specifically LLMs, to automate documentation and improve efficiency in healthcare business operations. The role involves designing and implementing ML models and NLP algorithms, conducting EDA, and leveraging LLMs for automation.

Data Architect to design the structural backbone of a high-scale, multi-modal healthcare data ecosystem, focusing on architecting data environments that serve AI agents and enable real-time clinical evaluation.

Lead the end-to-end development of AI agents within the Customer Success organization, focusing on identifying commercial opportunities, hands-on prompt engineering, and stakeholder alignment. This role bridges technical build teams and customer success to solve capacity and physician needs.