Fall 2026, Intern/Coop: Machine Learning Researcher

RTX•East Hartford, CT

2d•Hybrid

About The Position

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.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.