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It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies—like the da Vinci surgical system and Ion—have transformed how care is delivered for millions of patients worldwide.
We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.
The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.
If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.
Machine Learning Engineer - Robotics and Computer Vision
Intuitive
On-site
Sunnyvale, CA, United States
Full-time
$139,000 -
$201,000
About Intuitive
About the Role
The Ion™ endoluminal system is Intuitive's new robotic platform for minimally invasive biopsy in the peripheral lung, with an initial goal of improving the early diagnosis of lung cancer. The Ion R&D team is looking for a gifted engineer to contribute to our PlanPoint software and robot navigation, which together guide our physician users through the 3D structure of the lung, to take a biopsy at a target location. As a machine learning engineer on the Ion project, you will join a small team of experts in medical imaging, robotics, and software. You will play a lead technical role, working to conceptualize, design, and evaluate new solutions for medical image insights. You will contribute across the product development life cycle, taking algorithm concepts from initial prototypes to production software.
Qualifications
Master degree and 1 year experien
ce; or a PhD; or equivalent experience
Demonstrated expertise in medical image analytics, computer vision, or machine learning.
Exceptional working knowledge of Python and/or C++ programming.
Great communication, presentation, and documentation skills
High levels of autonomy and technical ownership.
Preferred Qualifications.
Expertise in object-oriented programming.
Knowledge of one or more of the following libraries and tools: PyTorch, TensorFlow, ITK, OpenCV, or other image insights toolkits.
Project experience in medical devices or another regulated industry.
ce; or a PhD; or equivalent experience
Demonstrated expertise in medical image analytics, computer vision, or machine learning.
Exceptional working knowledge of Python and/or C++ programming.
Great communication, presentation, and documentation skills
High levels of autonomy and technical ownership.
Preferred Qualifications.
Expertise in object-oriented programming.
Knowledge of one or more of the following libraries and tools: PyTorch, TensorFlow, ITK, OpenCV, or other image insights toolkits.
Project experience in medical devices or another regulated industry.
Responsibilities
Work as part of a cross-functional team in a fast-paced, start-up-like business unit.
Develop new algorithms and software implementations for computer vision, sensor fusion, registration, machine learning, etc.
Prototype and iterate on designs, develop tests, and deliver high-quality software in Python and/or C++.
Participate in failure mode assessment, to identify and implement robust hazard mitigation strategies.
Maintain practical knowledge of state-of-the-art computer vision and sensor fusion research literature.
Develop new algorithms and software implementations for computer vision, sensor fusion, registration, machine learning, etc.
Prototype and iterate on designs, develop tests, and deliver high-quality software in Python and/or C++.
Participate in failure mode assessment, to identify and implement robust hazard mitigation strategies.
Maintain practical knowledge of state-of-the-art computer vision and sensor fusion research literature.
