✦ Luna Orbit — AI & Machine Learning

Applied AI Engineer Co-op - Fall 2026 (September Start)

at General Electric

Remote 💰 $20 – $20 USD / year Posted April 15, 2026
Salary $20 – $20 USD / year
Type Internship
Experience intern
Exp. Years Not specified
Education Bachelor's degree program in Computer Science, Aerospace Engineering, Mechanical Engineering; or a related field at an accredited university or credentialed software accelerator program
Category AI & Machine Learning

As an Applied AI Engineer Co-op intern at GE Aerospace, you will build and deliver technical solutions that help engineers adopt data and AI approaches. You will work on projects spanning cloud platforms, data engineering, AI technologies, and numerical methods, collaborating with stakeholders to bring solutions to production.

  • Develop technical solutions for engineers to evaluate and adopt data and AI solutions
  • Consult on architecture, implement proof of concepts, and deliver solutions
  • Build and present product architectures; write code and demo applications to stakeholders
  • Use Innovator Method, Game Theory, and DecisionIQ to turn customer insights into solutions
  • Ship solutions to production that meet business needs

The role focuses on data and AI solution development, including consulting on architecture, building proof of concepts, and delivering machine learning systems and data science solutions. You will use Python and SQL (and potentially C#/C++) alongside cloud platforms such as AWS or Azure, applying methods like Innovator Method, Game Theory, and DecisionIQ.

The ideal candidate is a current undergraduate student pursuing a Bachelor's degree in Computer Science, Aerospace Engineering, Mechanical Engineering, or a related STEM field, with a strong academic record (minimum 3.7 GPA). They have hands-on experience building AI solutions such as Machine Learning, Large Language Models (LLMs), or Computer Vision, and can work with Python and SQL on data engineering and cloud platform projects.

PythonSQLMachine LearningLarge Language Models (LLMs)Computer Vision
proficiency in programming and debugging with PythonC#C++and SQLExperience designing AI solutions and architecting distributed data systemshands-on experience in at least one of the following areas: Machine LearningLarge Language Models (LLMs)or Computer VisionAWS and/or Azure certification
AWSAmazon Web ServicesAzureMicrosoft AzureDecisionIQInnovator MethodGame Theory
cloud platformsdatabasesdata engineeringweb designAI technologiesnumerical methodsInnovator MethodGame TheoryDecisionIQdata sciencemachine learning systemsproduct architecturesPythonC#C++SQLdistributed data systemsMachine LearningLarge Language Models (LLMs)Computer VisionAWSAzure
cloud platformsdatabasesdata engineeringweb designAI technologiesnumerical methodsdata sciencemachine learning systemsproduct architecturestechnical codePythonC#C++SQLdistributed data systemsMachine LearningLarge Language Models (LLMs)Computer VisionInnovator MethodGame TheoryDecisionIQAWSAmazon Web ServicesAzure
ability to lead design thinking workshopscustomer-centric mindsetcommunicationcross-functional collaborationinnovationdiversitydeep collaborationmentorshippresenting to stakeholders

Preferred

AWS and/or Azure certification
Industry Aerospace
Job Function Build and deliver AI and data engineering solutions as a remote co-op intern
Role Subtype AI Engineer
Tech Domains Python, SQL / PostgreSQL, Amazon Web Services, Azure, AI & Machine Learning
Applied AI Engineer Co-opAI Engineer Co-opCo-opinterncloud platformsdata engineeringmachine learning systemsdata sciencenumerical methodsPythonC#C++SQLMachine LearningLarge Language Models (LLMs)LLMsComputer Visiondistributed data systemsAWSAmazon Web ServicesAzureInnovator MethodGame TheoryDecisionIQdesign thinking workshopsstakeholders

Currently enrolled in a Bachelor's degree program in Computer Science, Aerospace Engineering, Mechanical Engineering, or a related field, Minimum 3.7 cumulative GPA off a 4.0 scale without rounding, Must be eligible for the internship (enrolled status implied by the posting)

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