Principal Computer Vision Engineer

As a valued member of Stryker’s AI innovation unit, you will work alongside trailblazers, industry visionaries, innovators, and inventors who are committed to bringing computer vision, AI/ML and digital innovation to the operating room and other healthcare settings. 

You’ll contribute to fast-paced cycles of innovation and develop core technologies that power a wide array of Stryker’s solutions, including: surgical robotics and navigation, image-guided surgery, treatment selection, outcome assessment, and clinical decision intelligence. You will apply your core skills across a range of deployment platforms spanning from mobile applications, cloud services, and SDKs to embedded systems, edge devices, and mixed reality (XR) platforms. You will have an opportunity to work across a wide variety of therapeutic areas ranging from orthopaedics and neurosurgery to emergency care and operating room safety and efficiency – plus many more.  

As a Principal CV Engineer/Scientist, you will play a crucial role in shaping the future of AI-enhanced healthcare. This high-visibility position offers an unparalleled opportunity for a technical leader who is passionate about diving deep into the intricacies of computer vision and deep learning problem-solving while making a significant business impact.  

Take the leap and join our elite team in the pursuit of revolutionizing healthcare technology. Apply now and become a driving force in the development and deployment of groundbreaking AI solutions!  

Responsibilities: 

• Work and collaborate with the CV/ML team to design, prototype, evaluate, optimize, implement and deploy CV/DL algorithms as an integral part of AI-powered medical technologies for the operating room. 

• Participate in cutting-edge research in computer vision that can be applied to AR/XR product development.  

• Design and develop novel computer vision and/or machine learning algorithms in areas such as: real-time object tracking, scene reconstruction and understanding as well as, segmentation, face tracking, body tracking, key point estimation, depth sensing, generative approaches such as GANs, 3D stereo and volumetric reconstruction, 2D / 3D medical imaging segmentation and rendering. 

• Research and prototype state-of-the-art computer vision and deep learning methods to develop solutions that meet product requirements.  

• Design algorithm evaluation frameworks, schedule and report algorithm performance evaluation on a regular basis.  

• Formulate processes for choosing appropriate sensors based on requirements like cameras and developing image processing algorithms, with an emphasis on classical computer vision, 3D geometry, and deep learning.  

• Document and present progress in algorithm design, development, and evaluation (requirements/design/architecture/bugs/tests).  

• Lead code reviews for projects/systems as an independent reviewer applying design principles, coding standards and best practices.  

Minimum Qualifications & Experience: 

•  ​Bachelor's degree in software engineering/ Computer Science or related discipline & 8+ years of work experience or Master’s / PhD degree in Software engineering/ Computer Science or related discipline & 6+ years of work experience
• Industry experiences working on projects such as: real-time SLAM and 3D reconstruction, sensor fusion and active depth sensing, object and body tracking and pose estimation, and/or image processing. Image and/or semantic segmentation, 2D and 3D key point estimation and surface reconstruction, depth estimation, generative methods such as GANs, or photorealistic rendering.  
• 4+ years of experience coding in Python.  
• Practical Experience with C/C++.  
• Experience with camera calibration, stereo vision, tracking, 3D points clouds, registration and associated algorithm development.   
• Experience with deep learning framework such as PyTorch, Tensorflow, Keras, Caffe, etc., for deep learning model training and deployment.   
• 3D Vision and projective geometry.  
• Computer Graphics.  
• Deep learning/machine learning for computer vision.  
• Practical applications of classical computer vision and machine learning techniques.  
• Practical experience with computer vision frameworks like OpenCV, Open3D, PCL, etc.   
• Experience in designing, training and deploying production-grade deep learning architectures for computer vision application with a broad under‐standing of latest 
• V / DL methods and literature.  
• Experience in writing reusable, scalable, test-driven and well documented codebase.  
• Excellent writing and verbal communication skills.