1 day ago
Base Salary
$195k - $330k/yr
Responsibilities
- Design, train, and evaluate deep learning models for semantic segmentation, object or structure detection, and surgical scene understanding from endoscopic imagery.
- Develop probabilistic modeling, statistical inference, optimization, and 3D spatial reasoning algorithms for complex clinical data.
- Build machine learning components that meet real-time performance constraints on embedded robotic platforms.
- Own the model lifecycle from research prototype through production, including architecture design, large-scale training, optimization, and integration with the da Vinci C++ software stack.
- Define clinically meaningful evaluation metrics, statistical validation frameworks, and testing approaches suitable for medical device regulatory submissions.
- Collaborate with surgeons, clinical scientists, human factors engineers, systems engineers, and software engineers to translate clinical needs into technical requirements.
- Mentor junior engineers and research scientists and establish practices for experiment tracking, model validation, and reproducible research.
- Contribute to intellectual property through invention disclosures and patent filings.
Requirements
- Required: M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, Biomedical Engineering, Applied Mathematics, or a closely related field with relevant graduate training.
- Required: 5+ years of post-Ph.D. or 7+ years of post-M.S. industry or applied research experience developing and shipping production-grade machine learning systems.
- Deep expertise in visual recognition and modern deep learning architectures, including semantic, object, or instance segmentation.
- Strong foundation in probabilistic modeling and Bayesian inference, including graphical models, nonlinear optimization, or MAP estimation.
- Proficiency in 3D geometry and spatial reasoning, including coordinate transformations, rotation representations, registration, and camera projection models.
- Hands-on production C++ experience, including navigating large codebases, prototyping, debugging, and interfacing machine learning models with C++ software.
- Experience optimizing and deploying models for latency-sensitive or embedded applications using ONNX, TensorRT, quantization, mixed-precision inference, or equivalent toolchains.
- Expert-level Python and PyTorch or an equivalent deep learning framework, with proficiency in NumPy, SciPy, and scientific computing at scale.
- Strong software engineering fundamentals, including version control, testing, code review, reproducible experimentation, and collaborative development.
- Track record of relevant publications or patents in computer vision, medical image analysis, surgical data science, robotics perception, or probabilistic modeling.
- Preferred: Experience with medical image analysis, clinical imaging modalities, annotation pipelines, statistical shape modeling, depth estimation, 3D reconstruction, numerical optimization, or regulated medical-device development.
- Preferred: Familiarity with FDA, ISO 13485, IEC 62304, design controls, verification and validation, and statistical testing plans.
Benefits
- Market-competitive compensation package including base pay, incentives, benefits, and equity.
- Fully onsite work arrangement with a day shift.
- Employee position; vaccination proof may be required for certain diseases depending on the role or customer.
- The role may be filled at a different job level based on business need and the candidate’s experience, knowledge, and skills.
- Compensation varies by job level, qualifications, and work region; listed target base-pay ranges span $195,200 to $330,400 USD annually.
Categories
ML EngineeringRobotics
About Intuitive
Intuitive (Nasdaq: ISRG), headquartered in Sunnyvale, Calif., is a global technology leader in minimally invasive care and the pioneer of robotic-assisted surgery. At Intuitive, we believe that minimally invasive care is life-enhancing care. Through ingenuity and intelligent technology, we expand the potential of physicians to heal without constraints.