Future Opportunity -- Machine Learning Engineer
Listed on Intuitive’s official careers site. Posted March 11, 2026. Check that it is still open and apply there.
Apply on Intuitive’s careers site →Job description
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. As an algorithms engineer on the Ion project, you will join a team of robotics and software experts. You will play a lead technical role, working to conceptualize, design, and evaluate new aspects of a guidance software solution. This role focuses on the processing and fusion of diverse imaging modalities—including CT, CBCT, X-ray fluoroscopy, and real-time camera video streams—to improve surgical navigation and clinical outcomes.
Drive the full cycle of the development of medical imaging analysis software, from clinical requirement analysis to production-ready code. Understand complex clinical requirements and develop detailed technical specifications. Design, prototype, and implement user-facing software and advanced algorithms for medical imaging, computer vision, and machine learning. Apply state-of-the-art techniques such as nnUnet, Vision Transformers (ViTs), DINO, Diffusion models, and Vision Language Models (VLMs) to endoluminal navigation challenges.
Support the development of AI/ML features in alignment with Good Machine Learning Practice (GMLP) principles, ensuring data representativeness and model transparency. Support system integration and testing while generating formal design documentation and patent applications
Qualifications
MS or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related quantitative field. 5+ years of hands-on experience in algorithm development with a specialization in medical imaging and computer vision. Proficiency in Python and C++, with a deep understanding of modern software component design. Expert knowledge of ML frameworks including PyTorch and OpenCV. Practical experience with specialized libraries including MONAI, SimpleITK, and VTK/ITK.
Hands-on experience with CUDA and model optimization tools such as TensorRT or ONNX. Deep understanding of GMLP guiding principles, including separation of training/test sets and performance monitoring for AI-enabled medical devices. Excellent verbal and written communication skills for effective cross-functional collaboration with clinical and engineering teams. Candidates at all experience levels are encouraged to apply, as the seniority level of the position may be adjusted based on the applicant.
Learn more about the compelling, collaborative work environment of the Ion Software Engineering Team here .
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