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.

The Senior Synthetic Data Engineer will architect and scale 3D synthetic data pipelines to accelerate the development of autonomous medical imaging systems. This role involves simulation, computer vision, robotics, and AI, focusing on generating high-fidelity synthetic data using platforms like NVIDIA Omniverse and Isaac Sim to enable robust AI model training through domain randomization, physics-based simulation, and real-to-synthetic data fusion.

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.

This is an apprenticeship role focused on integrating AI algorithms into a medical robot's software architecture. The role involves designing, implementing, training, evaluating, and integrating ML/DL models for perception, decision support, and control, while adhering to strict medical domain constraints (safety, traceability, real-time, regulatory). The work spans from algorithm development to deployment in a constrained embedded environment.

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.

Senior AI Engineer to lead the architecture and development of AI-powered automations combining LLMs, classical ML, RPA/workflow, and enterprise systems. The role involves designing reference architectures, building secure and performant services, and productionizing solutions, bridging solution architecture with hands-on engineering.