Principal Engineer - Learning for Dynamics & Control

RTX; East Hartford (CT); Hybrid; USD 108,000 - 205,000; Full time

Benefits offered by this job

Parental leave

Flexible schedules

Educational assistance

Scholar program

Job summary

RTX Technology Research Center (RTRC) seeks a Research Scientist in Learning for Dynamics and Control. This role targets developing cutting-edge control methods for aerospace and defense systems, combining ML with traditional control theory.

The position is hybrid, based in the United States, and involves collaboration with academia and government partners. The ideal candidate holds a PhD or MS with substantial industrial experience, and demonstrates expertise in model-based control, MPC, RL,

Qualifications

• PhD or MS in a relevant field with substantial industrial experience.
• Strong background in model-based control and optimization.
• Experience with ML for control, including RL and safety guarantees.

Responsibilities

• Design and develop control solutions for aerospace applications.
• Lead sponsored programs and write research proposals.
• Disseminate results via reports, conferences, and journals.
• Develop IP and collaborate across multidisciplinary teams.

Skills

Model-based control

Reinforcement Learning

Neural networks

Python

TensorFlow/PyTorch

Education

PhD in Math/Physics/CS/Engineering

MS in Math/Physics/CS/Engineering

Tools

MATLAB/Simulink

Python

PyTorch/TensorFlow

Job description

Location

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

Date Posted

2026-08-20

Country

United States of America

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.

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:
• optimization-based control, including Model Predictive Control (linear and nonlinear), from formulating the problem to implementation in software
• novel approaches for safety including Control Barrier Functions (CBF)
• standard multivariable control techniques
• estimation
• Experience with machine learning for control, including
• Reinforcement Learning (RL) for safety-critical systems (model-based RL, Sim2Real transfer learning, safety guarantee using CBF)
• Verification & Validation of AI/ML control laws (including but not limited to neural network-based control)
• 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
• Multi-agent autonomous behaviors
• 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
• experience with Speedgoat, dSPACE, or LabView/NIDAQ
• 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
• Robot Operating System and Gazebo simulation
• Open-source planning and perception software packages
• Commercial UAV and UGV platforms
• Experience with one or more of the following technical areas:
• Neural and symbolic AI approaches for course of action development
• Resilient contingency management for multi-agent autonomous systems
• Human-robot teaming
• Application experience in one or more of the following:
• Manufacturing and inspection operations
• autonomous systems, including assurance for autonomy
• safety and certification in aerospace
• gas turbine engine modeling and control;
• Guidance, Navigation, and Control (aircraft, spacecraft, or missiles) o hypersonic propulsion;
• electric or hybrid-electric propulsion for aircraft;
• 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

• parental (including paternal) leave
• flexible work schedules
• achievement awards
• educational assistance
• child/adult backup care

Compensation & Benefits

Salary range: 107,500 USD - 204,500 USD.

• 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
• holidays
• annual short-term and/or long-term incentive compensation programs

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.

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.

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.