Principal AI/ML Software Engineer

Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact. A Day in the Life At Medtronic, we value what makes you unique. Be part of a company that thinks differently to solve problems, make progress, and deliver meaningful innovations.  Our Purpose   The Interventional Cardiology Therapies (ICT) Operating Unit is dedicated to transforming care for patients with coronary disease and hypertension. We combine innovative devices, digital technologies, and advanced analytics and artificial intelligence to support clinicians and improve patient outcomes worldwide. The work you do will impact patients globally and help support Medtronic’s mission of alleviating pain, restoring health, and extending life.  The Principal AI/ML Software Engineer combines strong data science expertise with solid software engineering skills to design, build, and deploy production-grade machine learning systems. This role focuses on developing robust ML models and integrating them into scalable software systems that support real-world applications. Come for a job, stay for a career!    A Day in The Life Of:   As a Principal AI/ML Software Engineer , you will provide technical leadership in the design, development, deployment, and operationalization of machine learning and computer vision solutions that support connected healthcare technologies. You will work across the full AI lifecycle, from data exploration and model development through production deployment, monitoring, and continuous improvement, while partnering with cross-functional engineering and product teams to deliver scalable, reliable, and maintainable AI-enabled systems.

Computer Vision & Machi ne Learning Development  Design, develop, and evaluate computer vision and machine learning models to solve complex business and technical problems.  Perform data exploration, feature engineering, and model experimentation.  Apply appropriate validation and evaluation methodologies to ensure robust model performance.  Continuously improve models through experimentation and iterative development.  ML Systems and Production Deployment  Build end-to-end machine learning pipelines for data ingestion, training, validation, and deployment.  Deploy models into production environments as APIs, services, or batch processing pipelines.  Implement monitoring and performance tracking for deployed models.  Ensure reproducibility, versioning, and lifecycle management of ML models.  Software Engineering  Lead team to develop high-quality, maintainable, and testable Python code for ML systems.  Driving software engineering best practices including modular design, automated testing, and code review.  Design scalable services and components that integrate ML models into production applications.  Providing technical leadership to engineering teams to integrate ML capabilities into broader systems.  Infrastructure and MLOps  Work with cloud-based infrastructure to support ML training and deployment workflows.  Implement CI/CD processes for ML pipelines and model releases.  Support automation of model retraining and operational monitoring.  Ensure reliability, scalability, and observability of ML services.  Collaboration and Communication  Providing technical leadership to teams with data engineers, software engineers, and domain experts.  Translate analytical results into practical solutions and production-ready systems.  Influencing architectural discussions for AI-enabled platforms and products.  Working in agile/scrum framework and with cross-functional