Sr. Software Engineer

Role Summary

Design, implement, and optimize MRI image reconstruction algorithms and software, spanning classical methods (FFT/parallel imaging/compressed sensing) and deep learning-based reconstructions. Collaborate with physics, clinical, and platform teams to translate prototypes into clinical-grade products.

Key Responsibilities

• Feature and Algorithm Development: Implement MRI application feature, Design, implement, and maintain application services and APIs

• Deep Learning Recon: Build and train reconstruction networks (UNet/VarNet/physics-guided, score-based) using PyTorch/TF

• Performance Optimization: Improve performance, reliability, observability, and developer tooling, GPU/CUDA acceleration, multithreading, memory optimization for real-time/near–real-time recon

• Data Pipeline: Handle k-space data, calibration, coil combination, ESPIRiT maps, bias correction, post-processing

• Engineering Excellence: Write clean, testable code; unit/integration tests; CI/CD; containerization and deployment

• Standards & Integration: Work with DICOM/ISMRMRD; integrate with Gadgetron/BART/internal platforms

• Validation & Translation: Partner with MR physicists and clinicians for experiments, benchmarking, and productization
• Collaborate on architecture, technical roadmaps, and cross-team initiatives
• Participate in agile processes: planning, estimation, retros, and on-call (as needed)

Qualifications

• 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

Soft Skills

• Self-driven, outcome-oriented, turning research code into production

• Strong communication and cross-disciplinary collaboration

• Documentation and experiment reproducibility mindset

Inclusion and Diversity

GE HealthCare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership – always with unyielding integrity.

Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support.