AI Scientist

Job Description Summary

The Senior 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 Health Care, 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:

Job Description

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 GE Healthcare AI group. As the Senior Staff AI Scientist, you will focus on exciting generative AI problems, 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 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.

* 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 3 years of relevant research OR Ph.D. in a "STEM" major (Science, Technology, Engineering, Mathematics) or equivalent field with 3 years of relevant research.

* Publications as first author on LLM, Agentic AI or self supervised learning (SSL).

* Demonstrated expertise in building large scale AI such as generative AI models.

* 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 Deep Speed, Hugging Face, Megatron, PyTorch lightning, etc.

* Experience with various MLOps, Model Ops, 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

* Must be willing to travel to attend meetings, workshops, conferences & etc.

* Must be willing to work out of an office located in Bellevue, WA.

About Team

GE Healthcare teams are based in the US (San Ramon, Bellevue), France, Israel (Tel Aviv), and India (Bangalore). This gives us several core overlap hours for shared meetings.

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