This role is responsible for end-to-end AI algorithm integration, model conversion, quantization, and performance optimization for medical ultrasound systems
Job Summary
This role is responsible for end-to-end AI algorithm integration, model conversion, quantization, and performance optimization for medical ultrasound systems.
He/She will build efficient inference pipelines, collaborate with cross-functional teams, and enable reliable AI deployment on clinical imaging platforms.
GE HealthCare is a leading global medical technology and digital solutions innovator.
Matching Summary
This role is responsible for end-to-end AI algorithm integration, model conversion, quantization, and performance optimization for medical ultrasound systems.
Skills & Requirements
Must-have
AI algorithm integration
inference pipelines
deep learning models
model quantization
low-latency inference engine
Python and C/C++ programming
Nice-to-have
computer vision
computer graphics
image processing
teamwork and communication skills
Key Requirements
3+ years experience (Bachelor's)
2+ years experience (Master's)
Computer Science, Biomedical Engineering, Electronic Engineering or related fields
Experience in computer vision related CNN
Experience in inference engines (Onnxruntime, Tensor RT, OpenVino)
Familiar with deep learning model conversion, optimization, quantization, and acceleration