AI Assurance Research Engineer

Date Posted:

2024-12-04

Country:

United States of America

Location:

UT13: RC-CT - Corp 411 Silver Lane, East Hartford, CT, 06108 USA

Position Role Type:

Hybrid

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.  

To realize our full potential, RTX is committed to creating a company where all employees are respected, valued, and supported in the pursuit of their goals. We know companies that embrace diversity in all its forms not only deliver stronger business results, but also become a force for good, fueling stronger business performance and greater opportunity for employees, partners, investors, and communities to succeed.

The following position is to join our RTX Technology Research Center (RTRC) AI Systems Engineering team:

The AI Systems Engineering team researches and develops solutions using model-based system engineering, formal methods, planning, decision making, controls, machine learning, anomaly detection, computer vision, hardware-software co-design, and failure analysis techniques for a variety of high impact real world problems in the aerospace, manufacturing, and defense industries.

We are looking for an AI Assurance Research Engineer for the AI Systems Engineering team with passion for making safe and secure AI-enabled systems. The focus of this position will be to identify challenges in the development of dependable AI-enabled systems and create system engineering solutions for them.

You will get to develop state-of-the-art AI Systems tools and apply them to real world applications at scale. You will interact with and learn from leading researchers on a variety of topics working at RTRC.

You will work with a small and focused team engaged in a wide variety of research topics related to AI Assurance, Modelling and Design of Systems, Advanced Reasoning, Verification and Certification.

You will get to work on challenging problems within the broad areas of AI/ML applications in aerospace and defense.

We are looking for people who will thrive in a dynamic work environment and enjoy working on hard, cutting edge applied research problems for both our Business Units and government funding agencies. This position is performed with minimal supervision and requires a candidate with effective communication skills, a strong commitment for action, and the ability to prioritize and advance multiple objectives.

Role Overview

• The AI Systems Engineer will be responsible for one or more of the following activities:

• Conduct applied research in the formal analysis, design, verification & validation (V&V), test & evaluation (T&E), assurance, and certification of intelligent and autonomous aerospace systems as well as development of complex formal design, analysis, synthesis, V&V, assurance, and T&E tools.

• Initiate, lead, and execute on funding opportunities in both internal and external R&D.

• Keep abreast of the latest developments in the field by continuous learning and enthusiastically champion new ideas and new problem definitions.

• Work effectively in a multidisciplinary team environment focused on innovation and be able to partner with leading research institutions (universities, government agencies, national labs, and professional organizations).

• Demonstrate exceptional communication skills and ability to provide timely, accurate and detailed reports, presentations, and technical papers for archival journals.

Required Qualifications

• PhD in Computer Science, Engineering, Mathematics or a related field.

• Analytical, project management, problem-solving, interpersonal, leadership skills.

• Experience in any of the following: AI assurance, model-based design, logic, assurance cases, optimization, and system dynamics & control.

• Experience with formal analysis, verification tools and methodologies for cyber-physical systems including AI-enabled systems.

• Experience with AI technologies.

Preferred Qualifications:

• Experience with numerical computational