GE HealthCare Senior AI Scientist 

United States, Washington, Bellevue 

392614435

Roles and Responsibilities
Are you passionate about using AI to transform healthcare? We are looking for a highly motivated individual, passionate about foundational AI models to join the newly formed GE Healthcare AI group. As the Senior AI Scientist, you will focus on exciting generative vision, text, speech, time-series, and multi-modal problems related to segmentation, object detection, large-scale generative models, large-scale pretraining, prompt tuning, distillation, robustness, responsible AI, quantization, etc.
Additionally, you will be responsible for:
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

Eligibility Requirements

• Legal authorization to work in the U.S. is required. GE may agree to sponsor an individual for an employment visa now or in the future if there is a shortage of individuals with particular skills.
• Must be willing to travel to attend meetings, workshops, conferences & etc.
• Must be willing to work out of an office located in the greater Seattle Area.
• About Team
• GE Healthcare teams are based in the US (San Ramon, Bellvue), France, Israel (Tel Aviv), and India (Bangalore). This gives us several core overlap hours for shared meetings.
• Work/Life Balance
• Our team also puts a significant value on work-life balance. Having a healthy balance between your personal and professional life is crucial to your happiness and success here. We don’t focus on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work.
• Mentorship & Career Growth
• We maintain diverse engineering, and leadership perspectives and backgrounds across technology and beyond. Our employees are excited to share their experiences and mentor more junior engineers. Team members are highly encouraged to set up mentorship relationships with seasoned engineers, not only in our team, but also across the broader GE Healthcare population.