Machine Learning Researcher
Posted on 9/16/2025

RTX
Compensation Overview
$17.79 - $39.42/hr
Hartford, CT, USA
Remote
This position is remote.
Date Posted:
2025-09-12Country:
United States of AmericaLocation:
UT13: RC-CT - Corp 411 Silver Lane, East Hartford, CT, 06108 USAPosition Role Type:
RemoteU.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-120.62Security Clearance:
None/Not RequiredThe following position is to join our RTX Technology Research Center:
The Advanced Learning and Analytics 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, 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. We are looking for a fall co-op to support research on large language models (LLMs), focusing on areas such as reasoning capabilities, post-training techniques and detection/mitigation of vulnerabilities such as hallucinations.
What You Will Do
- Develop methods and algorithms to evaluate and improve LLM reasoning capabilities, post-training techniques (e.g., reinforcement learning, instruction tuning
- 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.
- 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 cutting-edge research in large language models, including reasoning, post-training, vulnerability detection/mitigation, and agentic AI.
- Strengthen hands-on skills in large-scale model training, evaluation, 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 a Ph.D. in Computer Science, Mathematics, or a related Engineering discipline. Candidates must not graduate prior to December 2025. Please submit a copy of your academic transcripts with your application.
- 1+ years of Ph.D.-level research experience in areas such as large language models, reasoning, post-training/fine-tuning techniques, or robustness/vulnerability detection.
- 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 AAAI.
- Demonstrated ability to set research direction, work independently, and contribute to collaborative team efforts.
Learn More & Apply Now!
Location: This position is remote.
Please consider the following role type definition as you apply for this role:
Remote: This position is currently designated as remote. Employees who are working in Remote roles will work primarily offsite (from home).
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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