GE Healthcare currently has 26 active job listings related to artificial intelligence. The majority of these roles, 50%, are focused on agents, with application roles making up another 23%. The company is primarily hiring for Engineering positions, with 18 listings in this function, and is recruiting in India and the United States. Frequent technology tags include agent_orchestration, fine_tuning, and rag. Over the last 30 days, GE Healthcare has posted 20 new AI roles, an 82% increase compared to the previous 30-day period.
GE Healthcare currently has 31 active AI-related roles in our index. The most common open titles are: Principal AI Architect (2), Senior Staff AI Scientist (2), Staff AI Scientist (2), AI / ML Architect, AI Algorithm and Development Software Engineer. Most positions are in Engineering and Research.
GE Healthcare's active AI hiring is concentrated in: agents (42%), application (23%), post-training (13%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
GE Healthcare is hiring AI talent in: India (14 roles), United States (4 roles), China (4 roles), South Korea (3 roles).
Job postings at GE Healthcare most frequently reference: model serving, fine tuning, agent orchestration, multimodal, rag.
In the past 30 days, GE Healthcare has posted 12 new AI-related roles. That is a -45% change versus the prior 30 days (22 → 12).
| Title | Stage | AI score |
|---|---|---|
| AI Research Intern PhD student intern focused on developing next-generation AI technologies for healthcare, including medical imaging foundation models and LLMs for clinical efficiencies. The role involves designing novel ML algorithms, building prototypes, and preparing research publications for leading AI venues. | Post-trainPretrain | 9 |
| Stage recherche appliquée en santé de la femme Research intern in Applied Research in Women's Health, focusing on mammography. Responsibilities include literature review, implementing identified methods, and validating results using signal processing and machine learning on mammography data. | Post-train |
| 7 |
| Software Engineer Software Engineer at GE Healthcare focused on building and training deep learning reconstruction networks (UNet/VarNet/physics-guided, score-based) using PyTorch/TF for CT applications. The role involves performance optimization, including GPU/CUDA acceleration and memory optimization for real-time processing, as well as engineering excellence in writing testable code, CI/CD, and containerization. It also includes integration with medical imaging standards and collaboration with physicists and clinicians for validation and productization. | Post-train | 7 |
| Software Engineer Software Engineer at GE Healthcare focused on designing, building, and optimizing MRI image reconstruction algorithms and software, including classical and deep learning-based methods. The role involves translating prototypes into clinical-grade products, improving performance, and handling data pipelines for MRI reconstruction. | Post-trainServe | 7 |