Principal Engineer - Learning for Dynamics & Control

Date Posted:

2026-08-20

Country:

United States of America

Location:

US-CT-EAST HARTFORD-RTRC L ~ 411 Silver Ln ~ RTRC L

Position Role Type:

Hybrid

U.S. Citizen, U.S. Person, or Immigration Status Requirements:

U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.

Security Clearance Type:

None/Not Required

Security Clearance Status:

Not Required

Are you ready to explore the world of aerospace and defense? Do you want to learn from and collaborate with some of the greatest minds in the industry? At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on complex problems, advance your skills and create a safer, more connected world. Discover opportunities to make a difference at RTX.

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Join us and help shape the future of aerospace and defense.

Background

The Dynamics, Control, and Autonomy Team, part of the Intelligent & Cyber-Physical Systems Department at RTX Technology Research Center (RTRC) is looking for a highly motivated individual for the position of Research Scientist in Learning for Dynamics and Control.

RTRC serves as the innovation hub for RTX. 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 transform that research into the solutions and products that help our businesses shape the future. We are:

Empowering innovation among the company’s businesses.

Solving customers’ critical problems.

Developing breakthroughs for a safer, more connected world.

Working with major universities and national laboratories on groundbreaking research.

The Dynamics, Controls, and Autonomy team supports dynamical system analysis and modeling, control system analysis and design, and autonomous systems research for all RTX business units, including both development of novel solutions for future products and solving the toughest problems with current products. In parallel, we are working with government customers on more broadly applicable technology.

What You Will Do

Design and develop novel control solutions for aerospace and defense applications including, but not limited to, jet engines, missiles, autonomous vehicles and systems, avionics, aircraft power systems and air management, hypersonic vehicles, advanced manufacturing, and space systems;

Work in a multidisciplinary setting, bringing system-level perspective to new cutting-edge technologies from multiple fields (autonomy, power systems, cyber security, mechanical systems, aerodynamics, thermal management)

Lead and support externally and internally sponsored programs, write external and internal research proposals;

Disseminate research results through reports, conference proceedings, and peer-reviewed articles, and developing intellectual property.

What You Will Learn

How to transition novel concepts from early technology stages to a state that impacts and influences our products, which in turn have global impact on society

How to build relationships both within our company, and externally with industry, academia, and government agencies for long-term impact

Qualifications You Must Have

Ph.D. in Mathematics, Physics, Computer Science or Engineering with 2+ years of professional experience, post-degree. MS in the above disciplines with 5+ years of full-time industrial experience may be considered.

Extensive experience in model-based control, including:

o optimization-based control, including Model Predictive Control (linear and nonlinear), from formulating the problem to implementation in software

o novel approaches for safety including Control Barrier Functions (CBF)

o standard multivariable control techniques

o estimation

Experience with machine learning for control, including

o Reinforcement Learning (RL) for safety-critical systems (model-based RL, Sim2Real transfer learning, safety guarantee using CBF)

o Verification & Validation of AI/ML control laws (including but not limited to neural network-based control)

o Neural-network representations of controllers and estimators (e.g., Physics-Informed Neural Networks for MPC, Neural Network based MPC)

Experience with multi-agent collaborative autonomy, including

o Multi-agent autonomous behaviors

o Decentralized mission planning and execution

Control-oriented modeling of physical systems, both from first principles and data-driven

Data driven includes learning-based methods (e.g. SINDy), Physics-Informed Neural Networks

Experience in MATLAB/Simulink, Python, PyTorch/TensorFlow

Qualifications We Prefer

Hardware-in-the-Loop validation and real-time/embedded implementation of control laws

o experience with Speedgoat, dSPACE, or LabView/NIDAQ

o FPGA programming

Hands-on experience with implementation of autonomy algorithms in high-fidelity simulations and/or hardware platforms: o PX4 or ArduPilot autopilots and software-in-the-loop simulations

o Robot Operating System and Gazebo simulation

o Open-source planning and perception software packages

o Commercial UAV and UGV platforms

Experience with one or more of the following technical areas:

o Neural and symbolic AI approaches for course of action development

o Resilient contingency management for multi-agent autonomous systems

o Human-robot teaming

Application experience in one or more of the following:

o Manufacturing and inspection operations

o autonomous systems, including assurance for autonomy

o safety and certification in aerospace

o gas turbine engine modeling and control;

o Guidance, Navigation, and Control (aircraft, spacecraft, or missiles) o hypersonic propulsion;

o electric or hybrid-electric propulsion for aircraft;

o control co-design

Experience with Large Language Models and agentic control

Experience with writing proposals for government-funded research, record of grants

a record of innovation as evidenced by patent applications, a track record of writing proposals for government funded research programs, and/or high-quality journal and conference publications.

Active Security Clearance

Additional Skills and Abilities

Strong analytical, problem-solving and interpersonal skills with track record of teamwork, adaptability, innovation and initiative

Clear and effective communication with all levels of management, business development, researchers and customers

Ability to focus on results in a fast-paced, dynamic team environment

Ability to work independently with limited direction and in multidisciplinary environment to accomplish project goals

The preferred candidate will look at open-ended tough problems as an opportunity to innovate and develop novel solutions

What We Offer: Whether you’re just starting out on your career journey or are an experienced professional, we offer a robust total rewards package with compensation; healthcare, wellness, retirement and work/life benefits; career development and recognition programs. Some of the benefits we offer include parental (including paternal) leave, flexible work schedules, achievement awards, educational assistance and child/adult backup care.

Please ensure the role type defined below is appropriate for your needs before applying to this role. This position is classified as:

Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.

If you live within a reasonable commute of an RTX site with other colleagues you interact with, your manager will discuss whether there is a degree of onsite presence associated with this role.

Candidates will learn more about role type and current site status throughout the recruiting process. For onsite and hybrid roles, commuting to and from the assigned site is the employee’s personal responsibility.

As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.

The salary range for this role is 107,500 USD - 204,500 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and key skills.

Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.

Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company’s performance.

This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.

RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.