Applied AI Intern

Job Description Summary At GE Aerospace, our AI engineers don’t just support projects — they help drive them. From day one, interns and co-ops take on real-world challenges, owning work from start to finish and building solutions that connect data, tools, cloud, AI, and engineering to advance the future of flight.

As an intern, you'll build expertise in cloud platforms, databases, data engineering, web design, Al technologies, and numerical methods to solve real-world engineering problems.

Through hands-on projects, you'll work with the Innovator Method, Game Theory, and DecisionIQ, turning customer insights into impactful solutions. You'll have the opportunity to learn, contribute, and bring real business value and help shape the future of aerospace design.

Job Description What You will Do • Develop technical solutions for engineers to evaluate and adopt data and AI solutions. • Consult on architecture, implement proof of concepts and deliver solutions for business strategic projects, including data science and machine learning systems.

• Build and present product architectures, write technical code, and demo applications to stakeholders. • Gain hands-on experience with the Innovator Method, Game Theory, and DecisionIQ and turn customer insights into solution that deliver real business value.

• Sharpen your skills in cloud platforms, databases, data engineering, web design, AI technologies, and numerical methods. • Use your strengths to support team members and build cross-functional relationships across the company.

• Work to ship solutions to production that meet business needs and drive impact. Our culture thrives on innovation, diversity, and deep collaboration.

You’ll contribute as both a learner and a builder, helping us push the design frontier in aerospace. Qualifications • Currently enrolled in a Bachelor’s degree program in Computer Science, Aerospace Engineering, Mechanical Engineering; or a related field at an accredited university or credentialed software accelerator program.

• Minimum 3.7 cumulative GPA off a 4.0 scale without rounding No prior work experience is required. Desired Characteristics • Strong academic performance in Computer Science or other STEM disciplines • Experience designing AI solutions and architecting distributed data systems • Proficiency in programming and debugging with Python, C#, C++, and SQL • Customer-centric mindset with ability to lead design thinking workshops • Hands-on experience in at least one of the following areas: Machine Learning, Large Language Models (LLMs), or Computer Vision • Experience building solutions using public cloud platforms such as AWS or Azure • AWS and/or Azure certification About The Internship • Location: Remote • Pay rates for this position begin at $20/hour and increase for each undergraduate year completed.

Relocation support and housing assistance is available for those who relocate to a new city. • Travel Opportunities • Real-world project ownership • Mentorship from experienced engineers • Opportunity for return offers Equal Opportunity Employer GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation.

GE Aerospace is an  Equal Opportunity Employer . Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

#LI-Remote - This is a remote position Additional Information GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation.

GE Aerospace is an  Equal Opportunity Employer . Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

GE Aerospace will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).

Employees may also be subject to random and reasonable-suspicion drug and alcohol testing.