Machine Learning Scientist, Generative AI

Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in the fundamental technology have finally allowed AI to significantly impact clinical care. Tempus' proprietary platform connects an entire ecosystem of tangible-world evidence to provide real-time, impactful insights to physicians. The platform delivers crucial information about optimal treatments for the right patients at the right time.

We are looking for a highly competent and innovative Generative AI Scientist to join our research and development team. In the role of a Generative AI Scientist, you will play a pivotal role in conceiving, creating, and executing cutting-edge generative artificial intelligence models and algorithms specifically designed for healthcare applications. Your work will contribute to the improvement of patient care, optimization of clinical workflows, and advancement of medical research. This position offers an exciting opportunity to use generative AI to revolutionize healthcare and make a significant difference in people's lives.

What you'll do:

• Develop LLM-based and generative AI agents that solve significant business challenges at Tempus across all our business units - touching on clinical notes, electronic health records, medical imaging, sequencing data, and so on.
• Healthcare-focused Research and Development: Conduct research and exploration of generative AI techniques, with a particular focus on healthcare applications. Keep abreast of the latest advancements in the field and adapt them to address healthcare-specific challenges, such as medical image generation, drug discovery, patient data analysis, or personalized medicine.
• Model Design and Development: Create and implement generative AI models designed for healthcare scenarios. Develop models capable of creating realistic and high-quality medical images, synthetic patient data, or generate text-based medical reports
• Experimentation and Evaluation: Plan and carry out experiments to evaluate the performance and effectiveness of generative AI models in healthcare settings. Develop relevant evaluation metrics that align with healthcare outcomes and clinical requirements. Collaborate with domain experts, clinicians, and researchers to verify and refine the models' outputs.
• Collaborative Teamwork: Collaborate closely with cross-functional teams, including healthcare professionals, data scientists, software engineers, and product managers. Use their expertise to guide your research, gain insights into real-world healthcare challenges, and translate your findings into practical solutions.
• Prototyping and Implementation: Create prototypes and proof-of-concept implementations of generative AI solutions for healthcare. Collaborate closely with engineering teams to integrate your models into healthcare platforms, systems, or applications. Ensure scalability, efficiency, and robustness of the deployed solutions.
• Regulatory Compliance and Ethical Considerations: Stay current with healthcare regulations, privacy laws, and ethical considerations relevant to the development and deployment of AI in healthcare. Ensure compliance with HIPAA, GDPR, and other applicable standards throughout the development process.
• Continuous Learning and Industry Engagement: Stay actively involved in the healthcare and AI research communities. Attend relevant conferences, workshops, and seminars. Publish research findings in reputable scientific venues. Collaborate with academic and industry partners to advance the state-of-the-art in generative AI for healthcare.

Qualifications:

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Biomedical Engineering, or a related field. A strong academic background with a focus on generative AI and healthcare applications is highly preferred.
• Extensive experience in developing and implementing generative AI models, such as GANs, VAEs, and related architectures.
• Proficiency in programming languages commonly used in AI research, such as Python and TensorFlow/PyTorch. Experience with healthcare-specific frameworks (e.g., DICOM, FHIR) is a plus.
• Solid understanding of machine learning concepts, including deep learning, optimization algorithms, regularization techniques, and model
• Bias-to-action, risk appetite for high risk projects with high returns with a practical approach to quick and measurable progress
• Strong track record in publications, patents, and/or launched products in this area

Nice-to-haves:

• Experience working with sensitive healthcare data, medical imaging modalities, clinical workflows, and healthcare terminology. Familiarity with electronic health records (EHRs) and medical imaging formats (for example, DICOM) is advantageous.
• Experience in late-stage startup environment
• Experience building and applying practical use, knowledge graphs, and graph-based machine learning models
• Expertise in embedding, multimodal fusion

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