Senior Machine Learning Engineer, Predictive Modeling & Applied AI

About the role

Join Flatiron Health's dedicated team to revolutionize cancer care through the power of data and advanced artificial intelligence. As a Senior Machine Learning Engineer specializing in predictive modeling and applied AI, you will be instrumental in developing sophisticated deep learning models that leverage real-world oncology data. Your work will directly impact how pharmaceutical and academic partners understand and treat cancer, by creating scalable, innovative solutions that improve patient outcomes. This role involves designing, implementing, and deploying models that can handle complex, multimodal datasets, and translating research into practical tools used in clinical and research settings. You will collaborate closely with cross-disciplinary teams to ensure that models are robust, reproducible, and aligned with organizational goals, all while staying at the forefront of AI advancements in healthcare.

Key facts

What you'll do

• Design, develop, and validate deep learning models utilizing oncology real-world data, including architectures such as transformers, foundation models, and neural networks tailored for multimodal data.
• Build predictive models for a variety of applications including digital twins, endpoint prediction, clinical trial optimization, and treatment effect estimation, ensuring they are scalable and accurate.
• Implement transfer learning and domain adaptation techniques to unify models across different data sources such as electronic health records (EHR), claims data, and other healthcare datasets.
• Collaborate with product managers, data scientists, engineers, and clinical experts to translate model prototypes into production-ready solutions that can be integrated into clinical workflows and research tools.
• Document model development processes thoroughly, including design decisions, validation procedures, and limitations, and communicate findings effectively to both technical teams and non-technical stakeholders.
• Stay abreast of the latest research and advancements in deep learning, especially in areas relevant to healthcare and oncology, and incorporate promising methodologies into ongoing projects.
• Transition models from experimental prototypes into scalable, maintainable production systems, ensuring reproducibility and compliance with healthcare standards.
• Contribute to the development of innovative solutions that address real-world challenges in cancer research, such as improving endpoint predictions or simulating patient responses.
• Support data-driven decision making by providing insights on model performance, robustness, and potential biases, and by advising on best practices for model deployment.
• Participate in cross-team meetings to align AI initiatives with organizational goals and ensure that models meet regulatory and ITAR requirements when applicable.
• Mentor junior team members and foster a collaborative environment focused on continuous learning and innovation.
• Engage in peer reviews of code and models to maintain high standards of quality, reproducibility, and scientific rigor.

Requirements

• An advanced degree (MS, PhD, or equivalent) in computer science, machine learning, applied mathematics, statistics, physics, or a related quantitative discipline, or equivalent industry experience.
• At least 5 years of professional experience developing, training, and deploying deep learning models in a healthcare or related domain.
• Strong expertise in modern deep learning techniques, including transformer architectures, foundation models, neural networks, and multimodal data processing.
• Proficiency in Python programming and hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
• Experience working with large-scale longitudinal healthcare datasets, such as electronic health records, claims data, or similar real-world data sources.
• Proven track record of taking models from research prototypes into production environments, emphasizing reproducibility, scalability, and maintainability.
• Excellent communication skills, capable of explaining complex technical concepts to diverse audiences including clinicians, researchers, and product teams.
• Ability to manage multiple projects simultaneously in a fast-paced, evolving environment, prioritizing tasks effectively.
• Knowledge of healthcare data privacy standards and familiarity with ITAR regulations when applicable.
• Strong problem-solving skills and a passion for applying AI to improve cancer care and patient outcomes.

Nice to have

• Experience working specifically with clinical oncology data, including understanding of relevant variables, study designs, and clinical endpoints.
• Background in developing digital twins, clinical trial simulations, or patient-level predictive models.
• Familiarity with causal inference methods and statistical techniques for longitudinal and time-to-event data analysis.
• Experience working with multimodal data types such as clinical text, medical imaging, or large language models for natural language processing (NLP) in healthcare.
• Prior deployment of AI models within regulated healthcare environments, ensuring compliance with industry standards and regulations.
• Contributions to scientific publications, conference presentations, or technical reports in the field of AI and healthcare.

Skills & tools

• Deep learning frameworks: PyTorch, TensorFlow
• Programming language: Python
• Data handling: Electronic health records, claims data, multimodal clinical datasets
• Data analysis and visualization tools as needed for model validation and reporting

Practical notes

This position offers a hybrid work arrangement, allowing you to work both remotely and on-site at our New York, NY office. You will spend three days in the office each week, with the flexibility to work from home on other days, based on team needs and personal preference. Flatiron Health provides a comprehensive benefits package designed to support your health, well-being, and professional growth. Benefits include flexible work hours, a competitive salary, 401(k) plan, financial health resources, mental health services, and parental leave. We are committed to fostering an inclusive environment that encourages innovation and continuous learning. For more details about our workplace culture, benefits, and life at Flatiron, please visit our Life at Flatiron page.