Staff Machine Learning Engineer

Role Overview

Responsibilities

• Design, train, and evaluate deep learning models for dense segmentation and structure detection from endoscopic imagery.
• Develop probabilistic, statistical, optimization, and structured inference methods for complex real-world data.
• Own models from research prototype through production integration with the da Vinci C++ software stack.
• Optimize models for latency-sensitive deployment using ONNX, TensorRT, quantization, or mixed-precision inference.
• Define clinically meaningful metrics and statistical validation methods for medical device regulatory submissions.
• Collaborate with surgeons, clinical scientists, human factors engineers, systems engineers, and software engineers.
• Mentor junior engineers and research scientists while establishing reproducible ML development practices.
• Contribute invention disclosures and patent filings in relevant technical areas.

Required Skills and Experience

• M.S. or Ph.D. in a relevant technical field with graduate training in computer vision, machine learning, probabilistic modeling, or 3D scene understanding.
• At least 5 years of post-Ph.D. or 7 years of post-M.S. experience developing and shipping production-grade ML systems.
• Deep expertise in visual recognition, including semantic segmentation, object detection, or instance segmentation.
• Strong foundation in probabilistic modeling and Bayesian inference, including graphical models, nonlinear optimization, or MAP estimation.
• Proficiency in 3D geometry, coordinate transformations, rotation representations, registration, and camera projection models.
• Working proficiency in production C++, including codebase navigation, debugging, prototyping, and ML software integration.
• Experience with model optimization and embedded or edge deployment for latency-sensitive applications.
• Expert Python and PyTorch or equivalent deep learning framework skills, plus NumPy and SciPy experience.
• Strong software engineering practices and a record of relevant publications or patents.

Preferred Skills and Experience

• Medical image analysis experience, including clinical imaging modalities and annotation pipelines.
• Experience with statistical shape modeling or methods for anatomical or biological variation.
• Familiarity with depth estimation, 3D reconstruction, or other 3D computer vision techniques.
• Experience applying numerical optimization to real-world engineering problems.
• Experience with regulated medical-device development, including FDA, ISO 13485, IEC 62304, design controls, and verification and validation.

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