Job Description Summary

We are looking to grow our Software Controls and Optimization team at GE Aerospace Research & are looking for top notch researchers to be part of this exciting journey. As a group, we innovate and execute on the R&D strategy for GE Aerospace on a range of problems from designing inspections solutions for aircraft engines to building predictive/prescriptive analytics for a variety of applications that improve process efficiencies in the business.

Job Description

As a Research Engineer - AI-Machine Learning, you will:

• Work independently as well as with a diverse team to develop and apply advanced technology solutions to GE Aerospace products and services using modeling, optimization, estimation, or detection technologies, leveraging AI/ML to augment a physics- based understanding of systems.
• Validate performance of developed solution through simulations and application on target product to mature technology to be transferred to the business.
• Document technology and results through patent applications, technical reports, and publications.
• Stay current with advances in system technologies to seek out new ideas and applications.
• Work in a team environment with colleagues across GE Aerospace Research, and business units.

• Doctorate degree in an Engineering field or a Master's degree in an Engineering field with a minimum of 4 years of background and experience in design of AI/ML algorithms.
• Strong background in machine learning, deep learning, data analytics.
• Proficiency in Python, C, C++, or Matlab.
• Self-motivated and ability to work independently and as part of a team.

• Demonstrated experience (algorithm development and software implementation) in developing systems solutions for complex physical systems.
• Strong analytical skills, familiarity with robust modeling/analysis techniques.
• Expertise in generative AI/Deep Learning techniques as applied to industrial data.
• Experience in training, fine-tuning, and deploying large language (and/or vision) models a plus.
• Knowledge and background in application of state-of-the-art NLP / Computer Vision algorithms to industrial data.
• Background in Knowledge Representation and Knowledge Graph technologies is a plus.
• Ability to communicate effectively with senior leadership.
• Demonstrated ability to take an innovative idea from a concept to a product.