Lead Scientist – Image Analytics

Job Description SummaryWe are looking for scientists in our AI Computer Vision team at our Technology and Innovation Center. As a group, we Innovate and execute around image analytics aligned our healthcare and industrial businesses in a broad set of areas including MRI, CT, Ultrasound, X-Ray for healthcare and automatic defect recognition, object recognition & tracking for industrial inspection and related applications.
GE HealthCare is a leading global medical technology and digital solutions innovator. Our purpose is to create a world where healthcare has no limits. 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

Roles & Responsibilities:

• Lead the ideation, development, and validation of novel AI-driven image analytics technologies for next-generation healthcare products, software, and services, with a focus on early-stage (low TRL) innovation.
• Design and develop state-of-the-art computer vision, image processing, signal processing, and machine learning algorithms for medical imaging modalities including MRI, CT, Ultrasound, X-ray, and physiological monitoring systems.
• Research and implement advanced deep learning and generative AI techniques—including diffusion models, GANs, foundation vision models, multimodal AI, and large language models—to address complex medical imaging and clinical workflow challenges.
• Develop physics-informed AI models by integrating domain knowledge of imaging physics with modern machine learning approaches to improve image quality, reconstruction, segmentation, detection, and clinical decision support.
• Build rapid prototypes, proof-of-concepts, and technology demonstrators to evaluate technical feasibility, performance, and potential business impact of emerging AI technologies.
• Collaborate closely with clinicians, product teams, engineering organizations, and business stakeholders to identify unmet needs and translate research outcomes into scalable healthcare innovations.
• Evaluate emerging research trends and technologies in computer vision, generative AI, multimodal learning, and medical imaging, identifying opportunities to create differentiated intellectual property and competitive advantage.
• Drive research excellence through publication-quality work, invention disclosures, patent generation, and technical leadership within the organization and the broader scientific community.
• Design rigorous experiments, establish validation methodologies, and benchmark AI models using appropriate datasets and clinical performance metrics to ensure scientific credibility and reproducibility.
• Contribute to the architecture and implementation of scalable AI solutions using modern deep learning frameworks such as PyTorch, TensorFlow, and Keras across diverse computing platforms.
• Mentor junior scientists and engineers by providing technical guidance, fostering innovation, promoting best practices, and cultivating a collaborative research culture.
• Partner with global cross-functional research teams to execute interdisciplinary projects that combine AI, imaging science, physics, software engineering, and clinical expertise to deliver breakthrough healthcare technologies.
• Support technology transfer by collaborating with product engineering teams to mature promising concepts from research prototypes toward commercialization.
• Champion scientific rigor, ethical AI practices, and regulatory awareness in the development of AI-enabled healthcare solutions.

Educational Qualifications:

• Masters / PhD in Electrical, Electronics, Mechanical or related Engineering field or Computer science/Biomedical engineering with specialization in image processing, signal processing, or inverse problems.
• Master’s degree holders with demonstrated research credentials in the fields of AI are also encouraged to apply. Specific areas of required expertise are: Image analytics, Deep Learning, Inverse problems in Imaging, Clinical decisioning, super resolution reconstruction.

Technical Expertise:

•  Expertise in Deep Learning and Computer Vision/ Image processing, TensorFlow, Pytorch and Keras is required.
• Experience with Generative AI techniques including diffusion models, GANs, foundation vision models, multimodal models, and large language models (LLMs). 
• Experience applying generative AI to medical imaging use cases such as image synthesis, image reconstruction, report generation, data augmentation, segmentation, and clinical workflow automation. 
• Familiarity with vision-language models (VLMs), retrieval-augmented generation (RAG), and multimodal AI systems for healthcare applications.
• Basic understanding of medical imaging or biology

Desired Characteristics:

• Strong foundations in design, analysis, and implementation of algorithms in different computing architectures is desired.

Leadership:

• Demonstrated skill at working in a team setting
• Demonstrated skill in critical thinking and problem-solving methods
• Demonstrated skill in presentation and influencing skills

Personal Attributes:

• Demonstrated skill in serving as a change agent
• Demonstrated skill in working in ambiguous environments

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