Responsibilities
- Design and train deep learning models quickly to address clinical challenges, including anatomical segmentation, object detection, and image quality enhancement.
- Lead the integration of artificial intelligence models and algorithms into current software systems and operational workflows.
- Work closely with data scientists, software engineers, and external partners to convert AI research into scalable, production-ready solutions.
- Build and sustain frameworks and tools that enable efficient deployment and management of AI models.
- Track and assess the performance of deployed AI systems, suggesting enhancements and optimization strategies.
- Enforce industry-standard best practices for AI integration, ensuring alignment with regulatory requirements and data protection standards.
- Produce and update comprehensive technical documentation covering integration procedures, system setups, and specifications.
- Modify advanced computer vision algorithms—such as U-Net, YOLO, and Transformers—for use with medical X-ray and video data.
- Support the creation of foundational data infrastructure by cleaning datasets, defining annotation guidelines, and curating training data.
- Acquire domain-specific knowledge of Interventional X-ray (Azurion) and clinical processes through on-the-job learning.
Work Arrangement
On-site
Team
This role emphasizes in-person collaboration, with expectations for regular on-site presence to support team cohesion and innovation.
Other
- 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.
- Indicate if this role is an office/field/onsite role.
- Strong communication skills in both English and Chinese.
