[Remote] Senior AI Solutions Architect - Industrial Engineering
Note: The job is a remote job and is open to candidates in USA. NVIDIA is a leader in computer graphics and AI technology, seeking a Senior Solutions Architect to support Industrial Engineering accounts. This role involves collaborating with engineering software developers and customer teams to enhance simulation performance and implement NVIDIA's advanced computing solutions.
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 (CAE/CFD/FEA ISVs, simulation platforms, and industrial OEMs)
- 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
Skills
- 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
- Experience GPU-accelerating CFD/FEA solvers, or developing physics-ML and surrogate models (NVIDIA PhysicsNeMo/Modulus, physics-informed neural networks)
- Experience with NVIDIA Omniverse, OpenUSD, and digital-twin workflows for industrial and engineering simulation
- Development experience with NVIDIA software libraries and GPUs, including CUDA and CUDA-X math libraries (cuBLAS, cuSPARSE, cuDNN)
- Experience with Kubernetes, distributed training, and large-scale inference
- Experience supporting or using PCIe accelerators such as GPUs, FPGAs, DSPs from evaluation to production stages
Benefits
- You will also be eligible for equity and benefits.
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