Staff AI Scientist

Job Description Summary The Staff AI Scientist will work in teams addressing statistical, machine learning and data understanding problems in a commercial technology and collaborative development environment. In this role, you will contribute to the development and deployment of modern machine learning methods for finding structure in large healthcare data sets.

At GE HealthCare, we are committed to bringing AI and cloud-based solutions for our customers: all aspects of computing services across the cloud and edge - including advanced analytics, visualization, multi-modal learning, servers, databases, storage, networking, analytics, software, intelligence are delivered over the Internet. Our Science & Technology organization is harnessing the power of technology to make healthcare more precise, more personalized, and more accessible for everyone. From driving the overall clinical research and patient-centric innovation strategy to delivering new digital and machine learning capabilities - we re committed to leading digital transformation, improving outcomes for patients and providers, and creating a world where healthcare has no limits. To find out more, visit: https: / / jobs.gecareers.com / science-technology

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 and Responsibilities

• Developing and implementing novel machine learning algorithms particularly in the area of LLM to provide automation of clinical tasks using one or more of medical images, electronic medical records, waveforms, and clinical reports.
• Demonstrating algorithms to meet accuracy requirements on general subject population through statistical analyses and error estimation.
• Exploring learning from human feedback and assisting humans evaluating AI.
• Building prototypes to enable development of high-performance AI algorithms in scalable, product-ready code.
• Initiating/proposing unique and promising deep learning capabilities, developing new and innovative algorithms and technologies, pursuing patents where appropriate.
• Working with large-scale datasets, designing, and developing generative algorithms.
• Staying current on published state-of-the-art algorithms and competing technologies.

Basic Qualifications

• Master s Degree in a STEM major (Science, Technology, Engineering, Mathematics) or equivalent field plus 5 years AI development for industrial applications in a commercial setting OR Ph.D. in a STEM major (Science, Technology, Engineering, Mathematics) or equivalent field plus 3 years AI development for industrial applications in a commercial setting OR Ph.D. in a STEM major (Science, Technology, Engineering, Mathematics) or equivalent field plus 1 years of AI development for Healthcare applications.
• Publications as first author on LLM/Foundational/Multimodal models or self-supervised learning (SSL).
• Demonstrated expertise in building large scale AI such as generative AI models, large vision/language models, and multi-modal AI models for problems related to segmentation, detection, quantification, measurements, classification, etc.
• Implementation experience with a variety of high-level languages (e.g. Python, C++)
• Experience with high-dimensional imaging data and waveform/time-series data.

Preferred Qualifications

• Experience and demonstrated capability to handle challenges with vague or abstract problem definition.
• Experience with frameworks and tools such as DeepSpeed, HuggingFace, Megatron, PyTorch lightning, etc.
• Experience with various MLOps, ModelOps, FMOps (Foundation Model Ops) methods.
• Experience working with large scale AI training.
• An in-depth understanding of machine learning algorithms and modeling (e.g., semi-supervised or weakly supervised learning, generative models, transfer learning, optimization, large language models, etc.)
• Track record in developing machine learning solutions using massive real-world data for solving real world business problems.
• In depth experience with Spark/Hadoop and either PyTorch/Tensorflow
• Experience creating production environment data analytics and applications

Additional Information