Enterprise robotics at Mayo Clinic spans clinical and surgical robotics and service and mobile robotics logistics, transport, environmental services, and patient-facing platforms delivered through multi-vendor fleets on a shared foundation of connectivity, data, security, and standards, and evolving from sensor-driven, deterministic robots toward AI-driven autonomous systems. The Principal Applied Robotics Engineer is the most senior capability-engineering individual contributor, exercising broad technical authority across multiple enterprise-critical initiatives for what robots can do for the enterprise and how their behavior is engineered. The incumbent sets the engineering direction for applied robotic behavior perception, navigation, manipulation, and autonomy across the portfolio and serves as the definitive technical resource for the hardest capability and feasibility problems. Working in close partnership with research scientists who own forward-looking research. The principal leads hands-on productionization and enterprise-scale evaluation of emerging capability without duplicating the research mandate, and partners with enterprise architects on standards. This is an individual-contributor role with no direct reports that provides broad functional and technical leadership while modeling stewardship, integrity, and a commitment to developing others in service of patients, staff, and the organization.
Bachelor's degree in robotics, computer science, computer engineering, electrical engineering, mechanical engineering, mechatronics, artificial intelligence/machine learning, or a related field and ten (10) years of progressively responsible relevant experience required, including demonstrated technical leadership of complex initiatives.
Master's or doctoral degree in a related field preferred.
Extensive, demonstrated authority engineering and evaluating robotic behavior and autonomy on physical platforms at scale is expected. Track record setting technical direction for perception, autonomy, or manipulation; deep simulation-to-reality and learning-based expertise, including approaches such as vision-language-action (VLA) and foundation models; leadership of emerging-technology assessment for humanoid and generalist systems; healthcare or comparable safety-critical settings.
The preferred candidate will possess:
Copyright © 2026 Grabjobs Pte.Ltd. All Rights Reserved.