NVIDIA is looking for a Solutions Architect to work in IPP's (Infrastructure, Planning and Process) Cloud Infrastructure Team. IPP is a global organization within NVIDIA. This group works with various other groups within NVIDIA such as Graphics Processors, Mobile Processors, Deep Learning, Artificial Intelligence and Driverless Cars to cater to their infrastructure needs. These cloud services provide almost half a million automated jobs per day on thousands of servers helping with the productivity of thousands of NVIDIA's software engineers worldwide. The cloud hosts a heterogeneous mix of machines and devices with various operating systems (Windows/Linux/Android), a multitude of hardware platforms both NVIDIA GPUs and Tegra Processors. Are you passionate about distributed infrastructure and looking for sophisticated, critical issues, ready to build the next generation of cloud services, design creative solutions, mine through data to uncover real problems and fix them?
What you'll be doing:- Work with NVIDIA Product Teams to understand new product roadmaps and requirements primarily Rack Scale AI Products.
- Finding Optimum Solutions to deploy these products in a Datacenter or a Lab environment using sophisticated design techniques, services and tools.
- Assist in roll-out and deployment of new development features aimed at supporting the latest NVIDIA hardware and technologies.
- Work closely with world-class engineers, architects, technical product managers and application developers setting the best strategies in place for a product launch.
- Defining and implementing full scale solutions for product onboarding into our hosted and private cloud environments.
- Solve sophisticated problems involving multi-site deployments of NVIDIA products and directly contribute to the overall quality of deployments and improve time to market next gen products.
- Collaborate with multi-functional teams, including system engineering, software engineering, mechanical/thermal engineering, operations, data center teams, external vendors, and other partners to successfully deliver a reliable and robust platform from concept to prototype to deployments.
- Integrate and Optimize Cluster Deployment methods and manage SW stack deployments, including provisioning these services into the cloud.
What we need to see:- Bachelor's or Master's Degree in Computer Science or Software Engineering, or equivalent experience.
- 12+ years of relevant experience.
- 6+ years of Linux and Scripting experience.
- Solid background on OS Kernels and system engineering.
- A track record of quickly understanding new technologies outside of your domain expertise and deploying systems in sophisticated configurations from hardware through multiple layers of software in a fast-paced environment.
- Strong technical skills and understanding of embedded systems, orchestration & automation systems, data centers and cloud architecture, as well as excellent communication and planning skills.
- Strong problem-solving ability and experience in product engineering/failure analysis and debug/ HW or test design.
- Understanding of dense datacenter design including compute, Storage and networking.
Ways to stand out from the crowd:- Understanding of software engineering principles and enterprise system architecture.
- Experience with gpu and compute clusters administration & automation.
- Experience in large scale QA environments, for product bring ups.
- Special skills in large-scale computing and cluster computing(MPI), data center design include high speed interconnect InfiniBand, Cluster Storage and Scheduling related design and/or management experience.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 333,500 USD for Level 5, and 256,000 USD - 414,000 USD for Level 6.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until February 1, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
