Staff AI Scientist, Foundation Models

As a Staff AI Scientist, Foundation Models, you will be a senior individual contributor focused on advancing large-scale foundation models for precision medicine. You will work at the intersection of machine learning, clinical science, and life sciences, developing novel models using one of the world’s largest clinical and molecular datasets and translating them into impactful applications across clinical research, drug development, and partner programs.

Key Responsibilities

• Technical Leadership: Serve as a senior individual contributor within the foundation model team, providing strong hands-on technical contributions while helping shape model architecture, research direction, and execution. Work closely with scientists and engineers to take ambitious AI technologies from research through validation and deployment.
• Foundation Model Research: Design, train, and advance state-of-the-art foundation models across large-scale multimodal clinical and molecular data, including longitudinal patient records, pathology, genomics, and related biomedical modalities. Drive innovation in areas such as pretraining, representation learning, self-supervised learning, multimodal learning, model scaling, and post-training.
• Foundation Model Applications: Develop and adapt foundation-model-derived models for downstream clinical and life sciences applications, including prognosis, treatment outcome prediction, patient stratification, biomarker discovery, clinical trial applications, and partner-specific AI solutions.
• Scientific Leadership: Contribute original ideas that advance Tempus’s foundation model research agenda, publish impactful research, and engage with the broader AI research community.
• Regulatory and Product Alignment: Work with cross-functional teams to ensure models and AI products meet appropriate quality, validation, and regulatory standards for healthcare and life sciences applications.

Qualifications

• Education: Ph.D. in Computer Science, or a related quantitative field.
• Professional Experience: 3+ years of industry experience driving end-to-end development of machine learning models, from research and experimentation to validation and production deployment.
• Domain Expertise: Demonstrated expertise in large-scale deep learning and foundation model development is required, including experience in areas such as pretraining, representation learning, self-supervised learning, multimodal modeling, or post-training. Experience with computer vision, NLP, pathology, longitudinal EHR, genomics, or other biomedical modalities is preferred. Prior work in medical or healthcare AI is highly valued but not required.
• Research Excellence: A strong track record of original, high-impact research demonstrated through peer-reviewed publications in leading machine learning, computer vision, NLP, or related AI venues is required. Publications in medical or healthcare AI and prior experience developing foundation models are strongly preferred.
• Engineering Excellence: Proficiency in Python and the modern deep learning stack (e.g. Pytorch). Strong product-level coding skills for model development are essential, along with a solid understanding of industry-standard software engineering and development practices.