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Other
postgraduate degree
Salary, Career Opportunities
Posted 44d ago
~40 hrs/week
Responsibilities
Design, develop, and deploy production-grade AI systems for medical imaging products, focusing on vision-language and diffusion models. Manage the end-to-end model lifecycle from data ingestion and training to deployment and monitoring.
Requirements
Requires a Master's or PhD in Computer Science, Electrical Engineering, or a related field with significant experience deploying ML systems to production. Proficiency in deep learning frameworks and software engineering fundamentals is essential, with medical imaging experience highly preferred.
Full job description
Job Description Summary
The Staff Machine Learning Engineer is a senior technical leader responsible for designing, developing, and deploying production-grade AI systems for GE Healthcare medical imaging products. This role focuses on vision-language models, diffusion models, and multimodal learning, working closely with data scientists, software engineers, product leaders, and clinical experts to turn advanced AI methods into robust product capabilities.
Job Description
The Staff Machine Learning Engineer is a senior technical leader responsible for designing, developing, and deploying production-grade AI systems for GE HealthCare medical imaging products. This role focuses on vision-language models, diffusion models, and multimodal learning, working closely with data scientists, software engineers, product leaders, and clinical experts to turn advanced AI methods into robust product capabilities.
Key Responsibilities
Design, implement, and productionize AI models for clinical applications, including vision and diffusion models.
Own end-to-end model lifecycle: data ingestion, training, evaluation, deployment, monitoring, and iteration.
Work with large-scale medical datasets, ensuring data quality, preprocessing, and efficient pipeline management.
Drive technical decisions and tradeoffs with a focus on scalability, maintainability, and real-world constraints.
Collaborate with clinical AI scientists to translate research innovations into production-ready solutions.
Stay current with advancements in vision-language modeling, GenAI, and related AI technologies.
Qualifications
Master’s or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or related field.
Significant hands-on experience building and deploying ML systems to production.
Strong experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow).
Solid understanding of deep learning, computer vision, and natural language processing techniques.
Prior experience working with medical imaging data is highly preferred.
Solid software engineering fundamentals, including testing, version control, CI/CD, and code reviews.
Independent, self-learner, and results-oriented.
Fluent English (speaking and writing).
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.
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.
A new era is here, and we want you to be a part of it. We will now be sharing our content on our respective GE Aerospace and GE Vernova pages. Be sure to follow each to keep up with the future of aviation and energy.
Offices: 41 Farnsworth St, Boston, MA 02210, US · 2 Whitefield Road, Bengaluru, Karnataka 560066, IN
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