Software Engineer

GE Healthcare GE Healthcare · Healthcare · Beijing, Beijing, China · Digital Technology / IT

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.

What you'd actually do

  1. Implement MRI application feature, Design, implement, and maintain application services and APIs
  2. Build and train reconstruction networks (UNet/VarNet/physics-guided, score-based) using PyTorch/TF
  3. Improve performance, reliability, observability, and developer tooling, GPU/CUDA acceleration, multithreading, memory optimization for real-time/near–real-time recon
  4. Handle k-space data, calibration, coil combination, ESPIRiT maps, bias correction, post-processing
  5. Write clean, testable code; unit/integration tests; CI/CD; containerization and deployment

Skills

Required

  • MS or PhD in CS, EE, Biomedical Engineering, Medical Physics, Applied Math, or related field
  • Strong math and signal processing foundation (linear algebra, optimization, Fourier/sampling theory)
  • Proficient in modern C++ with solid engineering practices
  • Knowledge of MRI reconstruction fundamentals: k-space, sampling trajectories (Cartesian/Spiral/Radial), parallel imaging
  • Expertise in at least one of: Optimization/Inverse Problems (ISTA/FISTA/ADMM/PGD), Parallel Imaging (SENSE/GRAPPA/ESPIRiT), Non-Cartesian Recon (NUFFT, Toeplitz/blocked-Toeplitz approaches), Deep Learning Recon (End-to-end or physics-constrained networks, Plug-and-Play)
  • Comfortable with Linux, Git, debugging, and performance profiling

Nice to have

  • CUDA/CuFFT/CuBLAS, OpenMP, SIMD vectorization
  • Experience with git, jenkens, devops, etc.
  • Hands-on with real MR data and sequences (EPI, 3D GRE/SE, VIBE, bSSFP, DWI/DTI, ASL, MRE)
  • DICOM/HL7, PACS/workstation integration, and medical software compliance (IEC 62304, ISO 13485)
  • Publications/competitions (e.g., fastMRI) or open-source contributions

What the JD emphasized

  • turning research code into production

Other signals

  • Deep Learning Recon
  • Performance Optimization
  • Data Pipeline
  • Validation & Translation