Applied AI Engineer (Hybrid)
Cedar Rapids, IAAll locationsCedar Rapids, IAUS-CT-FARMINGTON-0004 ~ 4 Farm Springs Rd ~ 4 FARM SPRINGSUS-AZ-TUCSON-863A ~ 1151 E Hermans Rd ~ 863AUS-NC-CHARLOTTE-2730 ~ 2730 W Tyvola Rd ~ TYVOLAUS-TX-MCKINNEY-513PW ~ 2501 W University Dr ~ PW BLDGUS-CA-EL SEGUNDO-E01 ~ 2000 E El Segundo Blvd ~ BLDG E01US-IA-CEDAR RAPIDS-105 ~ 400 Collins Rd NE ~ BLDG 105Farmington, CTSan Jose, CAMcKinney, TXAndover, MACharlotte, NC Hybrid
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About the role
We are seeking an experienced Applied AI Engineer to design, build, evaluate, and deploy production-grade Artificial Intelligence and Machine Learning solutions that address complex business and engineering problems across RTX.
What you'll bring
- This job requires a U.S. Person.
- 1101(a)(20) or who is a protected individual as defined by 8 U.S.C.
- 1324b(a)(3).
- For a complete definition of “U.S. Person” go here. https://www.ecfr.gov/current/title-22/chapter-I/subchapter-M/part-120/subpart-C/section-120.62
- At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems.
- With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can.
- Together, we push the boundaries of known science and find new ways to connect and protect our world.
- Join us and help shape the future of aerospace and defense.
- A University Degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related STEM discipline and a minimum of 8 years of relevant professional experience, or an Advanced Degree in a related field and a minimum of 5 years of relevant professional experience.
- A minimum of 3 years of hands-on experience developing, integrating, or deploying AI/ML solutions, including experience taking AI or ML capabilities beyond experimentation into production or production-like environments.
- Software engineering experience, including hands-on programming with Python and experience developing production-quality, tested, maintainable software.
- Experience building applications using Generative AI and large language models, including prompt or context engineering, model integration, structured outputs, retrieval, or tool use.