Senior ML Generative AI Scientist

As a Senior ML Generative AI Scientist at Tempus, you will be responsible for developing innovative generative AI applications tailored to our product line. This involves working with large, multi-modal datasets that include clinical, imaging, and molecular data. You will collaborate with cross-functional teams to ensure that the AI models align with our strategic objectives. Additionally, you will conduct research on generative AI techniques specific to healthcare, evaluate new technologies, and contribute to thought leadership by publishing findings.

To be successful as a Senior ML Generative AI Scientist at Tempus, candidates should hold a PostDoctorate or Ph.D. in fields like Computer Science or Artificial Intelligence. A strong academic background with a focus on generative AI and healthcare is preferred, along with at least 5 years of industry experience. Proficiency in programming languages such as Python and frameworks like TensorFlow/PyTorch is essential, as is familiarity with healthcare-specific frameworks.

Preferred candidates for the Senior ML Generative AI Scientist role at Tempus will have experience in a late-stage startup environment, working with sensitive healthcare data, and applying large language models to industry challenges. Experience in temporal modeling, multi-modal time series data, and developing knowledge graphs are advantageous. Being knowledgeable about medical imaging modalities and clinical workflows will also set you apart from the competition.

The Senior ML Generative AI Scientist at Tempus plays a vital role in enhancing patient care by designing AI models that optimize clinical workflows and improve the precision of medical treatments. By leveraging generative AI techniques, you will develop innovative applications that help physicians make informed decisions, ultimately contributing to better health outcomes for patients.

At Tempus, Senior ML Generative AI Scientists have abundant opportunities for professional development, such as attending conferences, workshops, and seminars to stay current with industry trends. You will also have the chance to collaborate with academia and industry partners to advance research, publish papers in reputable venues, and engage with the larger AI and healthcare communities.

When answering this question, focus on specific generative AI technologies you have worked with, such as GANs or VAEs. Discuss projects where you developed or fine-tuned models, emphasizing any unique applications you've created and the results achieved. Be sure to highlight any collaboration with cross-functional teams to underline your teamwork skills.

In responding, describe your methodology for setting performance criteria aligned with healthcare outcomes. Discuss your experiences with evaluation metrics and provide examples of how you have adjusted models based on patient care requirements or clinical workflows. Expressing your understanding of healthcare-centric challenges will showcase your relevant expertise.

To answer this question effectively, present a few current trends in generative AI, such as advancements in large language models or multimodal data integration. Tie these trends back to their potential applications in healthcare, discussing implications for improving diagnostics, personalized medicine, or streamlining clinical processes. This demonstrates both your knowledge and forward-thinking approach.

In your response, frame it as a storytelling opportunity. Choose a project where you worked with stakeholders or clinical teams to bridge the gap between AI technology and practical healthcare needs. Highlight your communication skills and how you gathered insights to refine your models, ensuring they met end-user requirements.

Address the specific challenges you've encountered, such as data privacy issues or integration with existing healthcare systems. Describe the steps you took to tackle these challenges, focusing on creative problem-solving and collaboration with interdisciplinary teams. Extract lessons learned to illustrate personal growth and adaptability.

When answering this question, be specific about the programming languages you've used, like Python, and the frameworks such as TensorFlow or PyTorch. Discuss specific projects where these tools were critical to your success and highlight any advanced techniques or libraries you employed, showcasing your technical acumen.

Discuss your methods for professional development, such as following industry journals, participating in online courses, or attending webinars and conferences. Mention specific sources where you gather information, reflecting a proactive commitment to continuous learning and staying relevant in a fast-evolving field.

Select a particular project that resulted in quantifiable improvements in patient care or operational efficiency. Outline your role in the project, the technologies used, and the outcomes. Emphasize how your solution addressed a specific healthcare challenge and improved the decision-making process for healthcare professionals.

Explain your understanding of ethical implications and considerations relative to AI in healthcare. Discuss approaches you take to prioritize patient safety, data privacy, and equitable access, as well as any frameworks or ethics boards you consult when developing AI solutions.

In your answer, share your vision for how you wish to contribute to the fields of AI and healthcare. Be specific about how you want to lead advancements, influence practical applications, or collaborate on groundbreaking research. This demonstrates ambition and alignment with Tempus' mission.