In this role you will be responsible for designing and programming a small module or a large component and designing a feature, set of features, or whole feature area. You will work independently and contribute to the immediate team and to other teams across business.
GE Healthcare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. 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.
- Define code architecture decisions to support a high-performance and scalable product with a minimal footprint for NLP platform team
- Build interactive data from multiple systems and RESTfully abstract to the UI through a Node.js backend
- Address and improve any technical issues
- Collaborate well with peer team members and architect to design and create advanced, elegant and efficient systems
- Hands on experience delivering microservices based architectures and design
- Hands on experience working with Kubernetes based applications and container workloads.
- Cloud Native (specifically good experience designing 12-factor apps)
- In depth understanding of Contract first/API first design and delivery experience. Strong experience in API design (OAS, middleware, external vs internal facing, etc.)
- Hands-on Full stack programming skills with expertise in Node
- Good understanding of various data design and deployment options on cloud – NoSQL, Relational, Scaling etc.
- ME/MTECH, PhD in Electrical Engineering/Electronics and communication engineering/Computer science/Biomedical engineering with specialization in image processing, signal processing, or inverse problems.
- Specific areas of expertise desired are: Medical Image analytics, Inverse problems in Imaging, Clinical decisioning, super resolution reconstruction.
- Expertise in at least one of C, C++, Python
- Strong foundations in design, analysis, and implementation of algorithms.
- Basic understanding of machine learning, computer vision or deep learning is preferred.