GE Healthcare

Chief AI Engineer at GE Healthcare to lead strategic development and implementation of AI initiatives in medical imaging and healthcare solutions, focusing on innovation, product performance, and ethical integration in regulated environments.

Technology Director for Connected Health & Artificial Intelligence at GE Healthcare's global innovation engine (HTIC). Responsible for shaping future technology roadmaps in digital health, multimodal data science, device-integrated AI, and clinical workflow intelligence. Drives innovation from research to impact, focusing on high-value AI capabilities, external partnerships, and scalable foundation technologies. Requires a Ph.D. and 10+ years of experience in AI research and development, with a proven track record in healthcare and securing external funding.

Software Engineer focused on developing and applying AI-assisted test automation and analysis solutions for patient monitoring systems within a regulated medical device quality environment. The role involves designing RAG models, agent workflows, and multi-step reasoning models, integrating LLMs into applications, and applying AI for root cause analysis and test selection to accelerate verification cycles.

This role focuses on ensuring AI-based clinical features for ultrasound systems comply with global regulatory requirements, particularly FDA regulations for AI-enabled medical devices. The AI Regulatory Engineer will define and execute AI regulatory strategies, risk management, and submission pathways across the full product lifecycle, working closely with AI engineering, clinical, quality, and product management teams.

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.