Solution Architect, Computer Aided Engineering
We are looking for a Solution Architect with deep expertise in AI solutions to drive the efficient use of groundbreaking compute platforms across industries. As a trusted technical advisor to our CAE developers and customers, you will be responsible for embedding NVIDIA software into developers' architectures and workflows.
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:
- A MS/PhD degree in Machine Learning, Computational Science, Physics, or a 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.
- Great teammate who can learn, react, and adapt quickly with a mentality to work for a fast-paced environment.
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.
XML job scraping automation by YubHub
