Job Description Summary
Women's Health and X-ray is pursuing a strategic initiative to unlock incremental revenue through the development of Digital SaaS solutions. These innovative applications will be layered onto the existing global install base of Mammography (Mammo), Digital Breast Tomosynthesis (DBT), and X-ray devices—transforming hardware into intelligent platforms that deliver enhanced clinical and operational value.
The Senior Synthetic Data Engineer will focus on architecting and scaling 3D synthetic data pipelines to accelerate the development of autonomous medical imaging systems. This role sits at the intersection of simulation, computer vision, robotics, and AI, with a strong emphasis on generating high fidelity synthetic data using modern simulation platforms such as NVIDIA Omniverse, Isaac Sim, and Cosmos. The engineer will enable robust AI model training by combining advanced domain randomization, physics based simulation, and real to synthetic data fusion.
This role evolves the traditional data engineering function toward simulation driven AI development, supporting perception, navigation, workflow automation, and autonomy in medical imaging environments (e.g., X ray rooms, scanners, and clinical workflows).
GE Healthcare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world.
Job Description
Key Responsibilities
In this role, you will:
Synthetic Data & Simulation Architecture
- Architect and maintain end‑to‑end 3D synthetic data pipelines for training and validating autonomous medical imaging and robotics systems.
- Design scalable simulation frameworks capable of generating large, diverse, and labeled datasets (RGB, depth, segmentation, keypoints, pose, sensor data).
- Leverage USD‑based workflows to build reusable, modular simulation assets and environments.
3D Simulation & Domain Randomization
- Create high‑fidelity 3D simulation environments representing medical imaging rooms (example X‑ray, fluoroscopy, etc.).
- Implement advanced domain randomization frameworks (lighting, materials, geometry, clutter, sensor noise, motion, human interaction) to improve model generalization and sim‑to‑real transfer.
- Develop procedural scene generation pipelines to explore all feasible room layouts and operational configurations.
AI Training Data Enablement
- Generate synthetic datasets optimized for computer vision, perception, and robotics AI models.
- Combine real‑world data with synthetic data (hybrid datasets) to improve model robustness and reduce data collection costs.
- Collaborate with ML engineers to align data generation strategies with downstream training requirements.
NVIDIA Omniverse & Ecosystem Integration (Highly Desired)
- Build and operate synthetic data workflows using NVIDIA Omniverse Replicator, Isaac Sim, and Cosmos models.
- Utilize NVIDIA Cosmos Diffusion models for scenario expansion, text‑to‑world, video synthesis, and multimodal data generation.
- Implement Cosmos‑in‑the‑loop simulation approaches to adaptively increase scenario complexity during training.
Human Modeling & Interaction (Highly Desired)
- Rig and animate 3D synthetic humanoids to model realistic clinical staff and patient interactions.
- Simulate human motion, posture, and interaction with medical imaging equipment for perception and safety‑critical AI use cases.
Collaboration & Technical Leadership
- Work closely with robotics, computer vision, safety, and product teams to support autonomous imaging initiatives.
- Document simulation architectures, data schemas, and best practices for reuse across teams.
- Influence technical strategy around synthetic data adoption for medical imaging autonomy.
Education & Experience
- Bachelor’s degree in Computer Science, Engineering, Robotics, or related STEM discipline (advanced experience required) with a minimum of 5+ years of experience into Software Development .
- Demonstrated experience in 3D simulation, synthetic data generation, or robotics/AI data pipelines.
Required Technical Skills
- Architecting 3D synthetic data pipelines for AI training.
- Creation of simulation‑based datasets for computer vision and robotics.
- Strong programming experience in Python (C++ a plus).
- Familiarity with physics‑based simulation and rendering concepts.
Highly Desired Skills & Experience
- NVIDIA Omniverse & Omniverse Replicator
- NVIDIA Cosmos, Cosmos Diffusion, Cosmos Transfer
- Rigging and animating 3D humanoids
- Hands‑on experience with USD (Universal Scene Description) workflows.
- Domain randomization and sim‑to‑real transfer techniques
- Integration of synthetic data with real‑world datasets
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.
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Additional Information
**Relocation Assistance Provided: **No