**Who this is for** This role is for an AI software engineer in WuXi passionate about developing deep learning solutions for medical ultrasound diagnostics. **
Work type: unknown
Location: WuXi
Type: Full-time
**Who this is for** This role is for an AI software engineer in WuXi passionate about developing deep learning solutions for medical ultrasound diagnostics. **Key highlights** You will manage the full model development lifecycle—from data processing and annotation to real-time model optimization—to improve clinical outcomes in lesion detection and image quality. **You might be a good fit if you...** - Have 2-3+ years of experience in AI, computer vision, or biomedical engineering. - Are proficient in Python and frameworks like PyTorch or TensorFlow. - Have practical experience with CNNs for classification, detection, and segmentation. - Enjoy collaborating with clinical teams to translate medical needs into technical AI features.
# Job Description Summary
This role is responsible for end-to-end development of AI models for medical ultrasound products, including data analysis and processing, model training, validation, and optimization. He/She will focus on building high-performance AI models for lesion detection, segmentation, measurement, classification and etc., and work closely with clinical and engineering teams to deliver AI solutions for Ultrasound users.
GE HealthCare is a leading global medical technology and digital solutions innovator. Our purpose is to create a world where healthcare has no limits. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world.tex
# Job Description
1. Design, develop, train, and optimize deep learning models for medical ultrasound images and video data, including lesion detection, segmentation, classification, anatomical measurement, image quality assessment, and real-time clinical guidance.
2. Perform ultrasound data processing, including data planning, cleaning, annotation standardization, dataset construction, and quality control for DICOM and clipping data.
3. Conduct model compression, acceleration, and optimization for deployment on ultrasound devices, cloud platforms, or edge computing systems.
4. Collaborate with ultrasound doctors, clinical applications, and product teams to define clinical requirements, validate model performance, and translate clinical needs into AI model design.
5. Track state-of-the-art research in medical imaging AI and ultrasound AI, and implement advanced technologies into product development.
6. Write technical documents, and supporting materials for product registration, clinical validation, and certification.
Qualifications/Requirements: