Principal Scientist, AI​/ML

At Edwards Lifesciences, the Advanced Innovation & Technology (AI&T) teams harness imagination, courage, and resourcefulness to think beyond what’s currently possible and create solutions for patients many years into the future. As part of AI&T, we're building an AI Center of Excellence (COE) focused on applying the power of AI to help patients live longer, healthier lives. As we expand our focus across the structural heart disease journey, AI is creating new opportunities to better understand and improve patient care.

Our teams are applying AI to support clinical decision-making, identify patients earlier, develop digital solutions that complement our therapies, and help employees work more efficiently so they can focus on work that matters most. We're building an AI COE that collaborates across our innovation-focused teams throughout our global organization, helping accelerate innovation and build AI capabilities that create lasting impact for patients, clinicians, and employees.

Together, we're committed to applying AI responsibly and thoughtfully while keeping patients at the center of everything we do. This is a rare opportunity to help define how AI is applied across the structural heart disease journey while shaping the next generation of therapies, digital solutions, and patient experiences. We’ll give you the tools and resources you need to create groundbreaking innovations that shape the future of structural heart technology.

As a Principal Scientist, you will help define the scientific and technical direction of AI across the structural heart disease journey. This role requires deep expertise in machine learning and scientific leadership, with the ability to evaluate new technologies, incubate novel capabilities, and guide teams developing AI-enabled products in regulated healthcare environments. Lead the design and development of scalable AI solutions that address complex business problems in partnership with business subject matter experts, product managers, data scientists, and engineering teams.

Lead the development of domain-specific foundation models across structured and unstructured clinical and procedural datasets, including natural language, medical imaging, and waveforms. Drive research and experimentation in generative AI, multimodal AI, representation learning, self-supervised learning, agentic systems, and advanced machine learning techniques. Ensure models are developed with appropriate rigor for generalizability, safety, fairness, robustness, and real-world performance. Identify, evaluate, and incubate new technology opportunities, including simulation, computational modeling, digital twins, physics-informed AI, scientific machine learning, and next-generation foundation models.

Deliver written quarterly technology-scouting positions that inform real investment decisions. Set scientific standards for the broader science group and provide technical leadership and mentorship to junior engineers and data scientists. Partner with engineering, quality, clinical, and regulatory teams to support development of AI-enabled products and digital solutions. Collaborate on model evaluation, validation, risk management, and deployment strategies for regulated healthcare applications.

Assess operational feasibility by evaluating problem definitions, analyses, requirements, solution development, and proposed solutions. Build and maintain robust data pipelines to train, test, and evaluate large language models (LLMs) and traditional machine learning models; engineer solutions using AI/ML frameworks and libraries. Stay current with generative AI and traditional AI/ML research and trends and incorporate relevant advances into product offerings. Improve and optimize model performance to ensure robustness, scalability, and efficiency.

Partner closely with AI Evaluation, Quality, Regulatory Affairs, and Software Engineering teams to support verification, validation, risk assessment, and regulatory documentation activities. Rigorously evaluate models for systemic bias and stand up MLOps frameworks to monitor performance drift or shifts across different datasets. Ensure code and model development are well documented and follow Edwards engineering practices.

Bachelor’s degree plus 6 years of experience in AI/ML engineering, with demonstrated success working with cross-functional IT and/or business teams on enterprise-level, complex, or novel system…