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# Sr. Machine Learning Engineer, Medical Imaging

- **Company:** Intuitive Surgical, Inc.
- **Location:** Sunnyvale, CA, United States
- **Experience:** Expert
- **Salary:** $240,700.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Algorithm Design, Computer Vision, C++ (Programming Language), Python (Programming Language), Machine Learning, OpenCV, Tensorflow, Systems Integration, Pytorch, Discretization, Information Technology, ONNX (Open Neural Network Exchange) Format, Hardware Acceleration, TensorRT
- **Published:** October 22, 2026
- **Apply:** https://jobs.smartrecruiters.com/Intuitive/744000156837940-sr-machine-learning-engineer-medical-imaging

## About the Role

* MS or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field.
 * 5+ years of hands-on industrial experience in algorithm development, with a deep specialization in medical imaging and computer vision. A proven track record of shipping commercial AI/ML software products is bonus.
 * Exceptional proficiency in Python and C++, with a deep understanding of modern software component design for production environments.
 * Proven hands-on experience with ML frameworks and software toolkits, including PyTorch, OpenCV, MONAI, ITK, VTK, and model optimization tools such as TensorRT or ONNX.
 * Experience or knowledge of the development of AI/ML features in strict alignment with Good Machine Learning Practice (GMLP) principles, ensuring data representativeness and model transparency.
 * Excellent verbal and written communication skills for effective cross-functional collaboration with clinical and engineering teams.

## Description

* Drive the full cycle of medical imaging analysis software development, developing algorithms from R&D concepts into robust, commercial medical device products.
 * Design, prototype, and implement advanced medical imaging and machine learning algorithms tailored for advanced lung structure segmentation, registration, target localization, respiratory anomaly detection, and bronchial analysis.
 * Apply and fine-tune state-of-the-art architectures, including nnU-Net, Vision Transformers (ViTs), DINO, Diffusion models, and Vision Language Models (VLMs), for clinical datasets.
 * Architect and execute model deployment pipelines, seamlessly integrating trained models into high-performance C++ production environments, utilizing techniques like quantization, pruning, and hardware acceleration to ensure real-time performance on constrained medical systems.
 * Support system integration and testing while generating formal design documentation and patent applications.