Advanced AI Engineer - Mechanical Engineering
Honeywell Aerospace
- Location
- Hybrid (Tempe, AZ)
- Employment
- Full-time
- Level
- Mid Level
About the Role
Honeywell Aerospace seeks an Advanced AI Engineer to develop physics-informed machine learning models and AI surrogates that accelerate engineering design and simulation workflows for aerospace mechanical systems.
Skills
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Short-term disability
- Long-term disability
- 401(k) match
- Flexible spending accounts
- Health savings accounts
- Employee assistance program
- Educational assistance
- Parental leave
- Paid holidays
- Paid time off
Perks
- Hybrid work
Full job details
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.