Staff Machine Learning Engineer

Job Description: We are developing next-generation AI and machine learning capabilities for the da Vinci robotic surgical platform. As a Staff Machine Learning Engineer, you will lead the design and development of perception and scene understanding systems that interpret surgical imagery in real time, enabling intelligent features that enhance surgeon awareness and decision-making during minimally invasive procedures. This role spans deep learning for surgical image understanding, probabilistic spatial modeling, and 3D scene reasoning. You will build ML systems that operate on endoscopic visual data and integrate multiple sources of clinical and anatomical information to support the surgical workflow. Your work will directly shape how our next-generation robotic systems leverage AI to improve the surgical experience and patient outcomes. We are looking for someone who is deeply product-oriented: you care about building systems that work reliably in the operating room, not just on a benchmark. You understand that the surgeon is your end user, and you are motivated by the clinical impact of helping them perform safer, more confident surgery on real patients.

What You'll Do: Design, train, and evaluate deep learning models for semantic understanding of surgical scenes, including dense segmentation and structure detection from endoscopic imagery. Develop structured modeling and inference approaches using statistical modeling, optimization, and related algorithmic methods for complex real-world data. Develop machine learning components and supporting algorithms that meet real-time performance constraints. Own the end-to-end model lifecycle from research prototype to production: architecture design, large-scale training, model optimization (ONNX, TensorRT, mixed-precision), and integration with the da Vinci C++ software stack. Define evaluation methodology with clinically meaningful metrics and statistical validation frameworks appropriate for medical device regulatory submissions. Collaborate with surgeons, clinical scientists, and human factors engineers to translate clinical needs into technical requirements. Partner with systems and software engineering teams to ensure ML components meet real-time latency, memory, and reliability requirements for deployment on embedded robotic platforms. Mentor junior engineers and research scientists; establish best practices for experiment tracking, model validation, and reproducible research. Contribute to intellectual property development through invention disclosures and patent filings.

Required Skills and Experience: M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, Biomedical Engineering, Applied Mathematics, or a closely related field, with graduate training involving computer vision, machine learning, probabilistic modeling, or 3D scene understanding.5+ years of post-Ph.D. or 7+ years of post-M.S. industry or applied research experience developing and shipping ML systems, with demonstrated impact on production-grade products or platforms. Deep expertise in deep learning for visual recognition, including semantic segmentation, object detection, and/or instance segmentation. Strong familiarity with modern vision architectures. Strong foundation in probabilistic modeling and Bayesian inference, including experience with one or more of: graphical models, nonlinear optimization, or MAP estimation for structured problems. Proficiency in 3D geometry and spatial reasoning: coordinate frame transformations, rotation representations (SO(3), quaternions, axis-angle), rigid and similarity registrations, and camera projection models. Hands-on experience with C++ development in a production context. Ability to read and navigate large C++ codebases, build system prototypes, debug C++ components, and interface ML models with C++ software stacks. Expert-level C++ is not required, but working proficiency is essential. Experience with model optimization and deployment for latency-sensitive applications: ONNX, TensorRT, quantization, mixed-precision inference, or equivalent embedded/edge deployment toolchains. Expert-level Python and PyTorch (or equivalent deep learning framework). Comfortable with NumPy, SciPy, and scientific computing at scale. Strong software engineering fundamentals: version control, testing, code review, reproducible experiment management, and collaborative development in a multi-disciplinary team. Track record of publications or patents in relevant areas (computer vision, medical image analysis, surgical data science, robotics perception, or probabilistic modeling).Preferred Skills and Experience Experience with medical image analysis, including familiarity with clinical imaging modalities and annotation pipelines. Experience with statistical shape modeling or related approaches for modeling anatomical or biological variation. Familiarity with 3D computer vision techniques such as depth estimation, 3D reconstruction, or geometric reasoning. Background in numerical optimization methods and experience applying them to real-world engineering problems. Experience developing ML systems within regulated environments (FDA, ISO 13485, IEC 62304), including design controls, verification and validation, and statistical testing plans for medical devices.

Additional Information: Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19. Details can vary by role. Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws. Mandatory NoticesU.S.

Export Controls Disclaimer: In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employeeswho are nationals from countries currently on embargo or sanctions status. Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government's licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan ("TCP") (note: typically adds 2 weeks to the hiring process). For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee'sstart date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes. We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws. Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee. This position may be filled at a different job level than listed here depending onbusiness need and/or on the selected candidate's experience, knowledge and skills. Compensation will be based primarily on the job level at which the role is filled and thecandidate's qualifications, consistent with applicable law. We provide market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity. It would not be typical for someone to be hired at the top end of range for the role, as actual pay will be determined based on several factors, including experience, skills, and qualifications. The target compensation ranges are listed.

Type: Full-time

Function: Engineering

Experience level: Associate

Industry: Medical Device