# Senior AI Solutions Architect - Industrial Engineering

**Company**: NVIDIA
**Location**: Santa Clara, CA
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-AI-Solutions-Architect---Industrial-Engineering_JR2020233-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_eb5bb891-829

## Description

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

## Skills

### Required
- CAE/CFD/FEA
- Computational Engineering
- Numerical Simulation
- Solver Development
- HPC-based Engineering Analysis
- Python
- C/C++
- GPU-accelerating Compute-intensive Workloads
- Accelerated Computing Platforms
- GPU-based Distributed Systems
- HPC Clusters/Schedulers
- Containers
- Numerical Libraries
- Modular Software Design
- Version Control
- GitHub

### Nice to have
- GPU-accelerating CFD/FEA Solvers
- Developing Physics-ML and Surrogate Models
- NVIDIA PhysicsNeMo/Modulus
- Physics-informed Neural Networks
- NVIDIA Omniverse
- OpenUSD
- Digital-twin Workflows
- NVIDIA Software Libraries
- GPUs
- CUDA
- CUDA-X Math Libraries
- Kubernetes
- Distributed Training
- Large-scale Inference
- PCIe Accelerators

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-AI-Solutions-Architect---Industrial-Engineering_JR2020233-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)