Advanced AI Engineer - Structural Analysis & Python

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.

Qualifications

• Bachelor’s degree from an accredited institution in a technical discipline such as science, technology, engineering, mathematics.
• At least 5 years of experience with Aerospace or Mechanical Engineering.
• At least 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.
• At least 3 years with simulation scripting (Abaqus Python scripting interface, Ansys PyAnsys or APDL or similar open-source tools).
• At least 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.
• 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.

Pay

The annual base salary range for this position is $185,000 - $ 231,000.

Schedule

Work from our Torrance, CA location on a Hybrid schedule. No Relocation Offered.