Breakthrough

Responsibilities

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.

Qualifications

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:

• Significant experience developing and productionizing robotic or autonomous systems, including experience with perception, navigation, manipulation, motion planning, and/or autonomous decision-making.
• Advanced programming experience in C++ and Python and demonstrated experience developing production-quality robotics software.
• Experience with ROS/ROS 2 and related robotics frameworks, tools, and ecosystems.
• Experience integrating and fusing data from robotic sensors such as cameras, depth cameras, LiDAR, force/torque sensors, or other sensing modalities.
• Experience with robotics simulation, testing, and validation technologies such as NVIDIA Isaac Sim, Gazebo, digital twins, hardware-in-the-loop, or simulation-in-the-loop environments.
• Experience with AI/ML techniques applied to robotics, including computer vision, robot learning, reinforcement learning, foundation models, or other approaches to intelligent autonomous behavior.
• Demonstrated experience evaluating the performance, reliability, safety, and failure modes of autonomous robotic capabilities in complex, dynamic, human-centered environments.
• Experience serving as a technical lead or senior individual contributor across multidisciplinary robotics initiatives, including translating emerging research into scalable, production-ready capabilities.
• Experience developing robotic or autonomous systems for healthcare, medical devices, logistics, industrial automation, or other safety- or mission-critical environments.
  
  

Exemption Status

Exempt

Compensation Detail

$185,244.80 - $277,867.20/ year. Education, experience and tenure may be considered along with internal equity when job offers are extended.

Benefits Eligible

Yes

Schedule

Full Time

Hours/Pay Period

80

Schedule Details

M-F daytime hours. This is a hybrid position and must be located within 100 miles of a Mayo Clinic campus. Onsite expectation will be as business needs dictate, but likely around once a month.

Weekend Schedule

NA

International Assignment

No

Site Description



Recruiter

Laura Percival