Fall 2026, Intern/Coop: Machine Learning Researcher

Date Posted:

2026-07-20

Country:

United States of America

Location:

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

Position Role Type:

Hybrid

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

Must be authorized to work in the U.S. without the company’s immigration sponsorship now or in the future. The company will not offer immigration sponsorship for this position.​ The company will not seek an export authorization for this role.

Security Clearance Type:

None/Not Required

Security Clearance Status:

Not Required

Are you ready to explore the world of aerospace and defense? Do you want to learn from and collaborate with some of the greatest minds in the industry? At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on complex problems, advance your skills and create a safer, more connected world. Discover opportunities to make a difference at RTX.

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.

The Artificial Intelligence team researches and develops machine learning, computer vision, reinforcement learning, large language models and human computer interaction solutions for a variety of high impact real world problems in the aerospace, manufacturing and defense industries. Examples include autonomy, multi-agent coordination, cybersecurity, material discovery and design. We conduct basic and applied research in a stimulating multi-disciplinary environment where scientists, engineers, practitioners, and subject matter experts collaborate and exchange experience.

We are looking for fall interns/coops to support research on large language models, with primary emphasis on agentic AI, reasoning models and verification/evaluation frameworks for LLMs and agentic systems.

What You Will Do:

• Develop methods and algorithms to evaluate, verify, and improve the reasoning, planning, and decision making of large language models and LLM-based agents.
• Design and run experiments on GPU cluster, and benchmark performance against established baselines.
• Explore approaches for agentic AI, including LLM agents that can plan, reason, and interact with tools and environments in a safe and reliable manner.
• Detect and mitigate vulnerabilities such as hallucinations and jailbreaks.
• Communicate research findings through presentations, technical reports, and contributions to top-tier publications.
• Collaborate with a focused team on topics including safe and reliable LLM deployment, vulnerability detection, and LLM agents, gaining exposure to cutting-edge Generative AI applications
   

What You Will Learn:

• Gain exposure to advanced research on LLMs and agentic systems, including planning, tool use, and interaction within complex environments.
• Strengthen hands-on skills in large-scale model training, evaluation, verification and safe deployment practices.
• Learn how to communicate research results effectively through presentations, technical writing, and potential contributions to top-tier AI/ML conferences.
   

Qualifications You Must Have:

• Currently pursuing an MS/Ph.D. in Computer Science, Mathematics, or a related Engineering discipline. Candidates must work a minimum of 6 months in co-op role. Please submit a copy of your academic transcripts with your application.
• 1+ years of MS/Ph.D.-level research experience in areas such as large language models, reasoning, post-training/fine-tuning techniques, robustness/vulnerability detection, formal verification
• 1+ years of machine learning software development experience in Python, with familiarity in deep learning frameworks such as PyTorch or TensorFlow.
   

Qualifications We Prefer:

• Publication record in top AI/ML venues such as NeurIPS, ICML, ICLR, ACL, or similar.
• Demonstrated ability to set research direction, work independently, and contribute to collaborative team efforts.

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.

Candidates will learn more about role type and current site status throughout the recruiting process. For onsite and hybrid roles, commuting to and from the assigned site is the employee’s personal responsibility.

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 at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.

The salary range for this role is 37,000 USD - 82,000 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and key skills.

Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.

Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company’s performance.

This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.

RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.

RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans’ Readjustment Assistance Act.

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