Sr/Staff ML Scientist, AI Research & Development

As a Sr/Staff ML Scientist at Tempus, your responsibilities will include developing innovative Large Multimodal models and generative AI applications that address impactful business challenges. You'll collaborate with cross-functional teams to understand requirements and ensure your algorithms align with strategic company objectives. Additionally, you'll work with one of the largest multimodal patient datasets, utilizing your expertise in healthcare data to guide optimal therapies and predictive modeling prototypes.

To successfully apply for the Sr/Staff ML Scientist position at Tempus, candidates should hold a Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related field with at least 8 years of industry experience. A strong background in large language models, generative AI, and experience with large-scale real-world datasets, particularly in healthcare, is highly preferred. Proficient programming skills in Python and SQL, along with familiarity with machine learning frameworks such as PyTorch and TensorFlow, are essential.

The Sr/Staff ML Scientist plays a pivotal role in advancing healthcare at Tempus by designing and developing state-of-the-art models tailored to healthcare applications. This position allows you to leverage unique datasets to make data-driven decisions that enhance patient care, optimize clinical workflows, and support ongoing medical research. Your contributions will help bridge the gap between AI technology and healthcare practice, leading to improved treatment outcomes.

Essential technical skills for the Sr/Staff ML Scientist role at Tempus include a deep understanding of machine learning concepts, particularly in large language models and transformer architectures. Candidates should have extensive experience with large-scale healthcare datasets and be proficient in programming languages like Python and SQL. Familiarity with machine learning libraries such as PyTorch and TensorFlow, as well as hands-on experience with model training frameworks, is also crucial.

At Tempus, the Sr/Staff ML Scientist will work on a variety of projects focused on developing Large Multimodal models and AI applications. These projects will encompass clinical notes, medical imaging, electronic health records, and genomic data analysis. You'll also have the opportunity to mentor junior team members and collaborate with experts across different business units to ensure that your work aligns with the company's strategic objectives.

When addressing your experience with large multimodal models, highlight specific projects where you've developed or applied these models in healthcare settings. Discuss the data sources you utilized, the challenges you faced, such as working with diverse data types, and the outcomes of your efforts. Be sure to emphasize how your work contributed to improving patient care or clinical workflows.

In answering this question, it’s important to convey your strategic mindset. Discuss how you evaluate project impact on business objectives, stakeholder needs, and resource availability. Use examples to illustrate how you've successfully managed competing priorities in previous roles, showcasing your ability to drive impactful results.

When discussing your methodologies for evaluating machine learning models, refer to the specific metrics and validation techniques you employ, such as cross-validation, A/B testing, or ROC AUC. Explain how you determine the effectiveness of models in real-world healthcare scenarios, emphasizing the importance of accuracy, interpretability, and scalability.

In your response, choose a particular data problem that highlights your analytical and problem-solving skills. Detail the nature of the challenge, such as dealing with missing data or unstructured data formats, and describe the steps you took to find a resolution. Also, mention what tools or techniques you leveraged and the end result of your solution.

Your response should demonstrate your commitment to continuous learning. Discuss resources such as academic journals, conferences, or online courses you follow. Mentioning engagement with community forums or professional groups can also emphasize your proactive approach to staying informed.

Communication is critical in the role of a Sr/Staff ML Scientist, as you'll need to explain complex technical results to varied audiences. Highlight your experience in creating presentations, writing reports, or leading discussions with both technical and non-technical stakeholders, focusing on how you've successfully facilitated collaboration and decision-making.

In discussing your experience with real-world healthcare data, outline the types of data you've worked with, such as electronic health records or sequencing data. Highlight the importance of understanding healthcare regulations and ethical considerations while providing examples of successful projects where you've utilized this data to influence healthcare outcomes.

When faced with a project that has unclear objectives, emphasize your approach to clarify requirements. Discuss techniques such as conducting stakeholder interviews, defining key metrics for success, and iteratively refining project objectives to ensure they align with business goals while still being flexible in your approach.

In discussing your mentoring or leadership experience, provide examples of how you've guided junior team members, managed cross-functional projects, or driven initiatives. Highlight outcomes from your leadership and how you fostered a collaborative environment that encouraged knowledge sharing and innovation.

When answering this question, consider challenges such as data privacy concerns, the need for regulatory compliance, and the importance of interpretability in AI models. Discuss your perspective on how overcoming these hurdles can lead to greater advancements and enhanced patient care within the healthcare sector.