PRINCIPAL R&D ENGINEER - DATA SCIENCE

Life Unlimited. At Smith+Nephew we design and manufacture technology that takes the limits off living!
We’re seeking a Principal R&D Engineer – Data Science who will serve as a leader in artificial intelligence—someone who not only understands where the field is today, but where it’s going next. In this strategic role, you will help drive S+N’s AI vision, ensuring we stay ahead of the curve by exploring, evaluating, and applying the most advanced technologies available. You will lead transformative AI initiatives that will shape the future of Smith + Nephew’s orthopedic, wound care, and sports medicine products. You will lead efforts to ensure S+N remains on the cutting edge – scouting emerging AI trends, evaluating breakthrough technologies, and turning them into real-world solutions that improve patient outcomes.
You will explore the frontier of AI—generative models, LLMs, deep learning, multimodal systems, and more — and apply these advancements to real-world healthcare challenges. You’ll work across R&D, engineering, and product teams to research, prototype, and scale next-generation AI-powered applications. Use your deep expertise to influence strategy, mentor others, and accelerate our mission to help patients live a Life Unlimited.

• Researching and evaluating pioneering AI technologies—including generative AI, LLMs, and deep learning—and identifying strategic applications in our product portfolio.
• Lead technology scouting initiatives and cultivate strategic collaborations with leading academic institutions, startups, and industry partners.
• Act as an inspiring leader in AI, driving S+N’s innovation strategy by scouting emerging technologies and translating them into impactful solutions across orthopedics, wound care, and sports medicine.
• Developing proof-of-concept models and scalable AI solutions to enhance decision support, personalization, and product performance.
• Designing and building advanced data pipelines, feature engineering workflows, and training datasets for sophisticated AI models.
• Leading development and validation of machine learning models using modern toolkits (e.g., PyTorch, TensorFlow) and statistical techniques.
• Creating intuitive tools and interfaces that allow partners to interact with, test, and deploy AI-driven applications.
• Collaborating across multidisciplinary teams to align AI strategy with business goals and regulatory frameworks.
• Mentoring junior team members and fostering a culture of innovation, experimentation, and continuous learning.
• Communicating complex AI concepts clearly to technical and non-technical audiences, including senior leadership.