Join NVIDIA as a Solution Architect, Computer Aided Engineering. In this role, you'll leverage deep expertise in AI solutions to drive the efficient use of our compute platforms across industries. You will act as a trusted technical advisor to CAE developers and customers, embedding NVIDIA software into their architectures to improve application performance, increase productivity, and build the technical foundation for next-generation AI systems.

What You'll Do

Support Business Development and Sales teams as part of a Team of 4, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive our developers’ ecosystem success.
Work directly with developers and customers in a customer-facing setting.
Support developers in adopting NVIDIA libraries and software frameworks as the foundation for modern AI and data platforms.
Analyze 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.

What We're Looking For

MS/PhD degree in Machine Learning, Computational Science, Physics or a related technical field.
A minimum of 5 years of technical experience in Physics-Machine Learning.
Experience in engineering simulations such as fluid dynamics, atmospheric science, or Computer-Aided Engineering technologies.
Familiarity with accelerated computing platforms and GPU-based distributed systems.
Experience in algorithm programming using languages like Python and C/C++.
Development experience using major AI frameworks like PyTorch and Tensorflow.
Familiarity with containers, numerical libraries, modular software design, version control, and GitHub.
Experience designing, prototyping, and building complex AI/ML-based solutions for customers.
Able to reason across components such as data pipelines, models, compute, networking, and orchestration.
Solid written and oral communications skills and familiarity with collaborative environments.
Great teammate who can learn, react and adapt quickly with a mentality to work for a fast-paced environment.

Nice to Have

Development experience with NVIDIA software libraries and GPUs.
Experience with Kubernetes, distributed training, and large-scale inference.
Experience supporting or utilizing PCIe accelerators such as GPUs, FPGAs, DSPs from evaluation to production stages.

Technical Stack

Python, C/C++, PyTorch, Tensorflow
GPU-based distributed systems, containers, numerical libraries
GitHub, Kubernetes

Team & Environment

You will be part of a Team of 4 Solution Architects, partnering closely with Industry Business leads, Account Managers, and Developer Relations managers.