Solutions Architect, AI & ML Infrastructure

Key Skills

Aartificial intelligence, CUDA kernels, Deep Learning, DevOps, Effective communication skills, GPUs, Linux Operating system, Machine learning techniques, MLOps tools, Presentation skills, SDK

Job Description

As part of the Solutions Architecture team, we work with some of the most exciting computing hardware and software technologies including the latest breakthroughs in machine learning and data science. A Solutions Architect is the first line of technical expertise between NVIDIA and our customers so you will engage directly with developers, researchers, and data scientists with some of NVIDIA’s most strategic technology customers as well as work directly with business and engineering teams on product strategy. We are looking for a Solutions Architect to help drive end-to-end technology solutions applying NVIDIA’s full set of technologies based on business needs of customers. Join us in this exciting endeavor!

What you will be doing:

• Working with Cloud Solution Providers on data center GPU server infrastructure projects.

• Help with cluster bring-up and deployment.

• Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and Data Center technologies

• Build custom PoCs for solution that address customer’s critical business needs applying NVIDIA hardware and software technology

• Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions for ML/DL and other software solutions

• Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.

• Conduct regular technical customer meetings for project/product roadmap, feature discussions, and intro to new technologies. Establish close technical ties to the customer to facilitate rapid resolution of customer issues

What we need to see:

• 5+ years of Solution Architecture Engineering or Software Engineering experience

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience.

• System level understanding of server architecture, PCIe devices, NICs, Linux OS and kernel drivers

• Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, Data Center deployments

• Good programming and debugging skills

• Ability to communicate your ideas/code clearly through documents, presentation etc.

Ways to stand out from the crowd:

• Hands-on experience with NVIDIA GPUs and SDKs (e.g. CUDA, RAPIDS, Triton etc.)

• System-level experience specifically GPU-based systems

• Experience in Deep Learning and Machine Learning

• Experience with Deep Learning at scale

• Familiarity with parallel programming and distributed computing platforms

We make extensive use of conferencing tools, but occasional travel is required for local on-site visit to customers and industry events. We are open to remote work location and look forward to have you join our team! NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

The base salary range is 144,000 USD - 224,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.