Agentic AI Researcher
Listed on 2026-06-01
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Software Development
AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer
Date Posted
CountryUnited States of America
LocationUS-CT-EAST HARTFORD-RTRC K ~ 411 Silver Ln ~ RTRC K
Position Role TypeHybrid
U.S. Citizen, U.S. Person, or Immigration Status RequirementsThis 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:
Security Clearance TypeNone/Not Required
Security Clearance StatusNot Required
RTX Corporation is an Aerospace and Defense company that provides advanced systems and services for commercial, military and government customers worldwide. It comprises three industry-leading businesses – Collins Aerospace Systems, Pratt & Whitney, and Raytheon. Its 185,000 employees enable the company to operate at the edge of known science as they imagine and deliver solutions that push the boundaries in quantum physics, electric propulsion, directed energy, hypersonics, avionics and cybersecurity.
The company, formed in 2020 through the combination of Raytheon Company and the United Technologies Corporation aerospace businesses, is headquartered in Arlington, VA.
Seeking a motivated and curious candidate for an Agentic AI Researcher position in the Advanced Learning and Analytics team, part of the AI Discipline. The Advanced Learning and Analytics team researches and develops machine learning, computer vision, reinforcement learning, LLM applications and human computer interaction solutions for a variety of high impact real world problems in the aerospace, manufacturing and defense industries.
Examples include autonomous flight, material discovery and design, automated visual inspection of parts, robotic perception and prognostics and health management. We conduct basic and applied research in a stimulating multi-disciplinary environment where scientists, engineers, practitioners and subject matter experts collaborate and exchange experience. This role focuses on creating grounded, explainable and verifiable AI systems capable of operating in complex high-stakes environments such as autonomous systems, command and control, decision support and safety critical domains.
You Will Do
- Design and build the next-generation agentic AI systems that combine the strengths of machine learning (LLMs, RL, deep learning) with symbolic reasoning, knowledge graphs and formal methods.
- Research, design and implement novel ML approaches for multi-modal data.
- Develop algorithms, publish and present your findings to both internal and external stakeholders.
- Initiate, lead, and develop capabilities by seeking funding opportunities through internal and external R&D.
- You will learn to collaborate and participate in a world class multi-disciplinary research environment working. Learn about challenges and help develop AI solutions in critical domains of aerospace and defense.
- B.S, M.S in Computer Science or a related field
- 3+ years of hands‑on experience in various ML techniques, off‑the‑shelf packages and development environments.
- Experience with building ML, LLMs and agentic systems and has a deep understanding of various ML and agentic frameworks like Pytorch, Lang Graph, Auto Gen
- Ability to understand and use details of an engineering problem statement, formulate it as an ML problem and identify candidate ML approaches.
- Research experience in synthesizing and combining multiple ML approaches to address novel engineering problems.
- Must be authorized to work in the U.S. without sponsorship now or in the future. RTX will not offer sponsorship for this position.
- Ph.D. in Computer Science or a related field
- 5+ years of professional ML experience with 2+ developing agentic solutions
- 5+ years of experience applying and adapting ML approaches from academic literature to real world problems.
- Experience with fine tuning LLMs for pushing the reasoning capabilities
- Prior experience in Aerospace and Defense applications
- Pub…
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