Work Flexibility: Hybrid We are on a mission to create groundbreaking artificial intelligence and computer vision solutions that transform medicine in operating rooms and hospitals worldwide. Be a part of the journey, apply now! Are you an outstanding Computer Vision (CV) and Machine Learning (ML) Deployment Engineer ready to make a lasting impact in the realm of AI-enhanced healthcare technology? Join our accomplished team and research, design, develop, and deploy innovative 2D/3D computer vision, augmented reality, mixed reality and deep learning-based algorithms into both existing and new medical device products. Your key responsibilities Lead software implementation of Computer Vision (CV) and Artificial Intelligence (AI) systems on edge devices (iPhone, iPad, Android Tablets, Nvidia platform, etc.) as an integral part of AI-powered medical technology platform for the operating room. Translate product feature requirements to design inputs / specifications and come up with high-level software design to meet requirements and guide design tradeoff decisions. Design algorithm evaluation frameworks, develop unit tests for algorithm components, schedule and report integration and system test performance on a regular basis adopting CI/CD principles for AI systems. Optimize and deploy algorithms (codebase, neural networks) on target hardware platforms, such as tablets and edge-computing devices to meet latency, memory, and performance requirements. Be the voice in the room that guides development work by ensuring work being done by the team is deployable in an end-to-end system. What are we looking for? You have several years of professional experience in implementation of computer vision, machine learning and deep learning algorithms onto edge environments such as iOS, Android and/or NVIDIA Jetson platform. Experience in developing AI/ML inference pipeline using CoreML, TFLite, TensorRT, etc. and demonstrated understanding of computer vision, image analysis, image registration, sensor fusion, machine learning and deep learning algorithm building blocks. Experience optimizing inference pipelines on edge devices and familiarity with ROS/2 and perception libraries, including but not limited to OpenCV, PCL, Open3D, etc. Demonstrated understanding of computer vision, image analysis, image registration, sensor fusion, machine learning and deep learning algorithm building blocks. You master the standard Software Development Life Cycle: knowledge in creating estimates for code implementation time/resource for assigned tasks and projects, and from using Application Lifecycle Management /Traceability tools as well as of regulatory and compliance standards applied to the SDLC (Software Development Life Cycle). Diversity is important to us. We welcome applications from people regardless of their ethnic, national or social origin, gender, disability, age or sexual identity. Additional information Thanks to our flexible working hours model, you will have the opportunity to work partially from the home office. A regular presence on site at our location either in Amsterdam should always be given to build sustainable relationships and maintain personal contact with colleagues as well as the departments. Your application We are looking forward to your online application including all relevant documents such as CV, transcript of results, and references. Please note to upload all attachments directly in our application procedure under the item "CV". Please note that the internal job title may differ from the ad title. Travel Percentage: 20% Stryker is one of the world’s leading medical technology companies and, together with its customers, is driven to make healthcare better. We offer innovative products and services in Orthopaedics, Medical and Surgical, and Neurotechnology and Spine that help improve patient and hospital outcomes. We are proud to be named one of the World’s Best Workplaces! For more information, visit: www.stryker.com Work Flexibility Remote – Role allows you to work the majority to 100% of time from an alternate workplace. These roles could have travel expectations, and you must work within the country of the job requisition location. Field-based – You can expect to regularly work a majority to 100% of time at customer facilities and has a set territory or expectation to travel within a set boundary. Almost all sales roles would likely be qualified as field-based. Onsite – Role is 100% located at a Stryker facility. Some ad hoc flexibility may be available depending on role, level, and job requirements. Manufacturing roles and any role that requires physical presence at the office would qualify under this category. Hybrid – You can expect to regularly work in both an alternate workplace and a Stryker facility. Roles that are partially remote or co-located would qualify as hybrid, and the expectation to be onsite would be defined and agreed upon by your manager/supervisor.