Principal Engineer, Optimization

Date Posted:

2026-07-14

Country:

United States of America

Location:

US-CT-EAST HARTFORD-RTRC L ~ 411 Silver Ln ~ RTRC L

Position Role Type:

Hybrid

U.S. Citizen, U.S. Person, or Immigration Status Requirements:

This job requires a U.S. Person. A U.S. Person is a lawful permanent resident as defined in 8 U.S.C. 1101(a)(20) or who is a protected individual as defined by 8 U.S.C. 1324b(a)(3). U.S. citizens, U.S. nationals, U.S. permanent residents, or individuals granted refugee or asylee status in the U.S. are considered U.S. persons. 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

Security Clearance Type:

None/Not Required

Security Clearance Status:

Not Required

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.

What You Will Do

• Provide technical expertise in the areas of discrete optimization, deep learning for computer vision, large language models (LLMs), vision-language models (VLMs), and state of the art methods for operations planning and scheduling. Of particular interest are demonstrated skills in these areas for industrial problems.

• Design and develop advanced optimization and machine learning solutions to complex decision-making problems in aerospace and defense applications.

• Develop and deploy deep learning models to solve challenging computer vision problems. Explore and integrate large language models (LLMs) and vision-language models (VLMs) for multimodal tasks.

• Lead and support externally and internally sponsored programs, writing external and internal research proposals.

• Build relationships to support developing business relationships with industry, academia, and government agencies.

• Disseminate research results through reports, conference proceedings, and peer-reviewed articles, and developing intellectual property.

 

Qualifications You Must Have

• Ph.D. in Operations Research, Computer Science, Applied Mathematics, or a related field, with minimum 5 years of industrial experience.

• Having expertise in one or more of the following areas: A strong background and understanding of mathematical programming such as discrete optimization and mixed integer programming; Expertise in designing and training deep neural networks for vision-related tasks; Familiarity with large language models (LLMs) and their integration into vision-language applications.

• Experience with Python, MATLAB, C++, or other programming languages and collaborative software development tools (e.g. Git).

Qualifications We Prefer

• Previous experience with practical applications in indicated fields with 10+ years of experience.

• A record of innovation as evidenced by high-quality journal and conference publications

• Ability to look at open-ended tough problems as an opportunity to innovate and develop novel solutions.

• Strong analytical, problem-solving, and interpersonal skills with track record of teamwork, adaptability, innovation and initiative.

• Clear and effective verbal and written communication skills.

• Ability to focus on results in a fast-paced, dynamic team environment

• Ability to work independently with limited direction and in multidisciplinary environment to accomplish project goals.

Learn More & Apply Now

Please ensure the role type defined below is appropriate for your needs before applying to this role. This position is classified as:

Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.

If you live within a reasonable commute of an RTX site with other colleagues you interact with, your manager will discuss whether there is a degree of onsite presence associated with this role.

As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person