Solution Architect, Computer Aided Engineering

Solution Architect, Computer Aided Engineering

Nvidia

Remote

We are looking for Solution Architects with deep expertise in AI solutions to drive the efficient use of groundbreaking compute platforms across industries. In this role, you will be a trusted technical advisor to our CAE developers and customers. You will be responsible for embedding NVIDIA software into developers’ architectures and workflows, you will play a direct role in improving application performance, increasing developer productivity, and establishing the technical foundation required for next-generation AI systems.

What you'll be doing:

• 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 need to see:

• MS/PhD degree in Machine Learning, Computational Science, Physics or related technical field.
• Minimum of 5 years of technical experience in Physics-Machine Learning
• Experience in engineering simulations (e.g. fluid dynamics, atmospheric science, 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 (e.g., PyTorch, Tensorflow, and similar tools)
• Familiarity with containers, numerical libraries, modular software design, version control, 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.

Ways to stand out from the crowd:

• 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.