AI Engineer - Medical Imaging & Surgical Robotics

AI Engineer – Medical Imaging & Surgical Robotics (Cambridge, MA)
Job Description

Join Philips to help shape the next generation of intelligent surgical robotics. In this role, you will work with robotics, software, and clinical experts to develop first-of-a-kind computer vision medical AI solutions that advance autonomy, decision-making, and workflow intelligence for image-guided procedures.

• Develop and apply AI and computer vision algorithms for medical imaging and image-guided surgical robotics applications.
• Design, train, evaluate, and optimize deep learning models, including convolutional neural networks, vision transformers, and other modern vision architectures for medical image understanding.
• Develop methods for object detection, segmentation, registration, image interpretation, tracking, and quantitative image analysis across medical imaging data.
• Work with imaging modalities relevant to image-guided therapies, such as X-ray, fluoroscopy, DSA, CT, CTA, CBCT, and related 2D/3D imaging sources.
• Contribute to multimodal sensing and image-based localization methods that support robotic perception, device awareness, and navigation workflows.
• Develop algorithms and software in a medical device environment, with attention to robustness, traceability, verification, and clinical relevance.
• Contribute to uncertainty estimation, safety monitoring, failure detection, and performance characterization for AI-enabled imaging and robotic systems.
• Partner closely with system engineering, robotics, software, clinical, regulatory, and product teams to translate algorithmic concepts into practical, production-oriented solutions.

• You have a Master’s degree with 2+ years of experience OR a PhD in Computer Science, Biomedical Engineering, Electrical Engineering, Robotics, Artificial Intelligence, or a related field.
• Your skills include:
  • You have strong experience in computer vision, medical image analysis, or machine learning applied to imaging data.
  • You have hands-on experience developing deep learning models using modern AI/ML frameworks, with practical knowledge of model training, evaluation, validation, and deployment.
  • You have experience with medical image processing techniques such as segmentation, registration, detection, tracking, feature extraction, or 2D/3D image analysis.
  • You are familiar with medical imaging modalities used in image-guided therapies, especially X-ray, CT, CTA, CBCT, 3D rotational angiography, or DSA. Prior experience with these modalities is highly preferred.
  • You have strong programming skills in Python. Experience with C++, software engineering best practices, CI/CD, and production-quality code is preferred.
  • You have experience, or strong interest, in uncertainty estimation, safety-bounded AI, runtime monitoring, robustness testing, or fail-safe behavior for AI-enabled systems.
  • You are comfortable working in a regulated medical device environment and can contribute to technical documentation, validation evidence, and cross-functional design discussions.
  • Publications or research experience in medical image computing, computer vision, or related venues such as MICCAI, IEEE TMI, CVPR, or similar are a plus.
• You must be able to successfully perform the following minimum Physical, Cognitive and Environmental job requirements with or without accommodation for this position.
• You possess excellent written and verbal communication skills and are self-motivated with good organizational and time management skills as well as a strong desire to learn and adapt to new technologies and challenges.

We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. Onsite roles require full-time presence in the company’s facilities. Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.

This is an office role.

We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we…