About this role
Job title: Staff Machine Learning Engineer
About the Role 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.
What You'll Do
- 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.
What We're Looking For
- 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).