Summer 2026 - Agentic AI Intern (Onsite)

RTX•East Hartford, CT

1d•$37,000 - $82,000•Onsite

About The Position

The Advanced Learning and Analytics team researches and develops solutions in machine learning, computer vision, reinforcement learning, large language models, and human-computer interaction for a variety of high-impact, real-world problems in the aerospace, manufacturing, and defense industries. Examples include autonomy, multi-agent coordination, cybersecurity, and 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 share expertise. We are seeking summer interns to support research on large language models, with a primary focus on agentic AI, reasoning models, and verification/evaluation frameworks for LLMs and agentic systems.

Requirements

Currently pursuing a Ph.D. in Computer Science, Mathematics, or a related Engineering discipline, with graduation no earlier than December 2026. Please include a copy of your academic transcripts with your application.
At least 1 year of Ph.D.-level research experience in areas such as large language models, reasoning, post-training/fine-tuning techniques, robustness/vulnerability detection, or formal verification.
At least 1 year of experience in machine learning software development using Python, with familiarity in deep learning frameworks such as PyTorch or TensorFlow.

Nice To Haves

A strong publication record in top AI/ML venues such as NeurIPS, ICML, ICLR, ACL, or AAAI.
Proven ability to set research direction, work independently, and contribute effectively to collaborative team efforts.

Responsibilities

Develop methods and algorithms to evaluate, verify, and enhance reasoning, planning, and decision-making capabilities of large language models (LLMs) and LLM-based agents.
Design and execute experiments on GPU clusters, benchmarking performance against established baselines.
Explore approaches for agentic AI, focusing on LLM agents capable of planning, reasoning, and interacting with tools and environments in a safe and reliable manner.
Detect and mitigate vulnerabilities, including hallucinations and jailbreaks.
Present research findings through presentations, technical reports, and contributions to top-tier publications.
Collaborate with a dedicated team on topics such as safe and reliable LLM deployment, vulnerability detection, and LLM agents, while gaining exposure to cutting-edge Generative AI applications.