Senior AI Solutions Architect - Industrial Engineering

NVIDIA is seeking a Senior Solutions Architect to support Industrial Engineering accounts, including CAE, CFD, and FEA software vendors, engineering-simulation platforms, and industrial OEMs. The successful candidate will be a trusted technical advisor to simulation and engineering software developers, embedding NVIDIA accelerated computing, Omniverse, and physics-ML into solver, simulation, and digital-twin pipelines.

Responsibilities:

• Support Business Development and Sales teams as part of a small Solutions Architecture team, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive ecosystem success across Industrial Engineering accounts.
• Work directly with engineering-software developers and customer simulation teams in a customer-facing setting.
• Help developers GPU-accelerate and scale CAE/CFD/FEA solvers and structural, thermal, and fluid-dynamics workloads on NVIDIA accelerated computing and HPC platforms.
• Apply physics-informed ML and surrogate modeling (e.g., NVIDIA PhysicsNeMo / Modulus) and NVIDIA Omniverse digital twins to compress design, simulation, and optimization cycles.
• Analyze simulation and engineering application architectures and find opportunities for acceleration.
• Provide feedback and collaborate with engineering, product, and research teams.
• Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms.

Requirements:

• MS/PhD in Mechanical, Aerospace, Civil, or Chemical Engineering, Computational Science, Applied Mathematics, Physics, or a related technical field (or equivalent experience).
• 4+ years working in CAE/CFD/FEA or computational engineering , numerical simulation, solver development, or HPC-based engineering analysis.
• Hands-on experience with commercial or open-source simulation tools (e.g., Ansys, Siemens Simcenter, Altair, COMSOL, Cadence Fidelity CFD, OpenFOAM, LS-DYNA, Abaqus).
• Strong grounding in numerical methods (FEM/FVM/spectral), linear algebra, and the mathematics behind physics solvers.
• Experience in algorithm programming using languages like Python and C/C++, with familiarity GPU-accelerating compute-intensive workloads.
• Familiarity with accelerated computing platforms, GPU-based distributed systems, and HPC clusters/schedulers (e.g., Slurm).
• Familiarity with containers, numerical libraries, modular software design, version control, GitHub.
• Experience designing, prototyping, and building complex solutions for customers; able to reason across components such as data pipelines, solvers, compute, networking, and orchestration.
• Solid written and oral communication skills and familiarity with collaborative environments.
• Team player who can learn, react, and adapt quickly, with an attitude to work in a fast-paced environment.

Benefits:

• Equity
• Benefits