As an Advanced AI Engineer at Honeywell Aerospace, you will provide technical contributions to the development of AI-driven engineering design tools and physics-based machine learning models. This role focuses on applying artificial intelligence, physics-informed methods, and surrogate modeling to accelerate the design and analysis of aerospace mechanical systems, including wheels and brakes, fuel systems, environmental control systems, and other complex components. You will help shape the next generation of simulation and analysis capabilities by integrating AI with traditional computational tools such as CFD, FEA, and multi-physics solvers.
In this role, you will develop advanced AI surrogates and Physics-AI models, and contribute to the transition these technologies into engineering workflows across Honeywell Aerospace. You will collaborate with cross-functional teams and global research partners, pursue both internal and government research funding, and contribute to the execution from concept through integration. Your work will impact engineering efficiency, product performance, and Honeywell's leadership in AI-enabled engineering design.
Key Responsibilities
Contribute to the creation of advanced Physics-AI models and surrogate models to accelerate engineering workflows for CFD, thermal analysis, structural analysis, and system-level simulation.
Create scripted FEA or CFD models to generate training data over parameter and load condition spaces.
Suggest ideas to drive the AI strategy for engineering design, with a focus on physics-informed neural networks (PINNs), digital twins, and high-fidelity model surrogates.
Research and test new AI methodologies for multi-physics modeling of aerospace components such as engines, wheels and brakes, and mechanical actuation systems.
Suggest improvements to current processes for efficient data generation, data handling, and model utilization.
Utilize and advance state-of-the-art NVIDIA simulation and AI acceleration tools, including Physics NEMO and related model-based AI frameworks.
Collaborate closely with engineering teams to integrate surrogate models into design processes, enabling faster trade studies, optimization, and predictive analysis.
Contribute to technical execution across internal and government-sponsored R&D projects and contribute to proposal development.
Assist with outreach to traditional design and analysis engineering functions.
YOU MUST HAVE
Bachelor's degree from an accredited institution in technical disciplines such as the sciences, technology, engineering or mathematics.
2 years of experience developing AI models for physics-based simulation, engineering analysis, multi-physics modeling, or surrogate modeling. Experience in a graduate program may be included.
3 years with simulation scripting (Abaqus Python scripting interface, Ansys PyAnsys or APDL or similar open-source tools).
5 years working on design and simulation of physics of engineering systems involving concepts such as Computational Fluid Dynamics or Structural Analysis
Experience mentoring others in specialty areas.
Experience with NVIDIA's physics-accelerated AI tools such as Physics NEMO, Modulus, Warp, or similar platforms for physics-informed deep learning
WE VALUE
Bachelor's or Master's degree in aerospace engineering, mechanical engineering, or a related engineering discipline.
Proficiency in Python and machine learning frameworks such as PyTorch and TensorFlow.
Experience with JAX for differentiable models
Experience working in structured machine learning deployment environments i.e. MLOps workflows
Experience with CFD, structural analysis, thermal modeling, or multi-physics simulation, and the ability to couple these with AI-based surrogates.
Experience with AI model architectures used for surrogate modeling, such as but not limited to MeshGraphNets, Neural Operators, Physics-Informed and Physics-Attention models.
Experience with model visualization through tools such as PyVista, Matplotlib, Plotly, and others.
Awareness of considerations for deploying AI models into engineering design workflows or digital engineering ecosystems.
Awareness of current research in physics-informed ML, scientific machine learning, and surrogate modeling at major conferences and journals.
ABOUT HONEYWELL AEROSPACE
Join a company that's reintroducing itself to the aviation community we've helped advance for more than a century. At Honeywell Aerospace (NASDAQ: HONA), we're launching as an independent, publicly traded aerospace and defense company built on a legacy of operational excellence and mission-focused execution.
Our new brand identity pairs that heritage with real momentum, as we build technology that helps pilots navigate with confidence, aircraft operate more efficiently, and operators stay ahead of change. With our systems on board 90% of the world's aircraft, your work here has reach, that's rare to find anywhere else.
Focusing on our customers, investing in innovation, and building a culture of accountability and performance is how we're shaping what comes next.
Every horizon. Every mission. Every day.
BENEFITS OF WORKING FOR HONEYWELL AEROSPACE
Beyond a performance-driven salary, you'll work alongside dedicated experts on technology that's advancing aviation. As a Honeywell Aerospace employee, you're eligible for a comprehensive benefits package that includes:
Employer-subsidized medical, dental, vision and life insurance
Short-term and long-term disability coverage
401(k) match, flexible spending accounts and health savings accounts
Employee assistance program and educational assistance
Parental leave and 12 paid holidays
Paid time off for vacation, personal and sick time
Explore your benefits: https://honeywellaerospacebenefits.com/
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Job Posting Date: August 6, 2026
Sponsorship
We are currently not sponsoring applicants for work visas for this position. Applicants must be currently authorized to work in the United States on a full-time basis.
LI-Hybrid
U.S. PERSON REQUIREMENTS
Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status.
