AI Machine Learning Data Analytics Principal Engineer - P4 (Remote)

RTX•East Hartford, CT

1d•$107,500 - $204,500•Remote

About The Position

At RTX, the world 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. Pratt & Whitney is a world leader in the design, manufacture and service of aircraft engines and auxiliary power systems and has been revolutionizing modern flight for over 100 years. Join us and help shape the future of aerospace and defense. This role is Remote: Employees who are working in Remote roles will work primarily offsite (from home). 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. Hot Section Engineering (HSE) Hot Section Engineering is responsible for the design, development, technology maturation and in service support of all diffuser cases, combustors, turbines (vanes, blades, rotors and cases), augmenters (military), nozzles and associated fuel systems for all military, commercial and industrial engine models and radial auxiliary power units. Technical disciplines in HSE include Project Engineering, Mechanical Design, Structural Analysis, Durability and Product Definition. RTX 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, Pratt & Whitney, and Raytheon. Its 195,000 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, Virginia.

Requirements

Bachelor’s degree in Science, Technology, Engineering or Mathematics (STEM)
8 years of engineering experience, or an Advanced degree in a related field and 5 years of related engineering experience.
U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.

Nice To Haves

Master’s degree or PhD preferred in Engineering, Computer Science, Physics, Mathematics, or related technical field or equivalent experience.
Familiarity with high-performance distributed computing
Knowledge of state-of-the-art architectures, machine learning techniques, and algorithms with experience developing or using major deep learning frameworks (e.g., PyTorch, Tensorflow, JAX)
Experience with solving and using machine learning for real world problems involving scientific & engineering simulations (e.g., structural, CFD, thermal)
Strong Python programming skills and SQL proficiency
Publication record in the field of scientific machine learning / AI4Science
Experience with gas turbine engines or airbreathing propulsion applications
Demonstrated understanding and of uncertainty quantification (UQ) and statistical inference techniques

Responsibilities

Work with the AI/ML team to develop and apply novel machine learning frameworks and methodologies supporting the design and evaluation of turbine components for the Hot Section Engineering organization.
Deploy AI/ML applications and/or agentic workflows within Hot Section processes and tools.
Communicate technical solutions and insights to internal/external customers and organization leadership.
Advocate for and participate in fundamental AI/ML research via with our academic and external research institute partners.
Collaborate with RTX AI/ML teams to strengthen the corporate level AI/ML initiatives and infrastructure.