Senior Physics‑Informed AI Engineer for Aerospace Design

Honeywell Aerospace US LLC in

Tempe (AZ)

On-site

USD 120,000 - 190,000

Full time

14 days+

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Benefits offered by this job

Medical, dental, vision insurance

Disability coverage

401(k) match

Educational assistance

Parental leave and paid holidays

Paid time off

Job summary

Honeywell Aerospace is seeking an Advanced AI Engineer - Mechanical Engineering to develop AI-driven tools that accelerate design and analysis of aerospace systems, including engines, wheels and brakes, and environmental controls. You will integrate AI with CFD/FEA and multi-physics solvers, and work with cross-functional teams and research partners to push the boundaries of physics-informed engineering.

Responsibilities include creating Physics-AI models, generating training data via scripted

Qualifications

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.
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

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.