Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Launch your career as a Solutions Architect at NVIDIA. In our 15-month New College Graduate Rotation Program, you’ll work alongside expert engineers and customer-facing teams to tackle real technical challenges. You’ll help customers bring workloads to life using NVIDIA’s hardware and software—and build the skills to become a trusted technical advisor. Every quarter, you’ll rotate into a new team and explore areas such as hyperscalers, AI factories, NVIDIA Cloud Partners, healthcare, automotive, robotics. Along the way, you’ll gain hands-on experience, learn from experts, receive feedback, and discover where your strengths and interests can have the greatest impact. By the end of the program, you will gain broad experience across NVIDIA’s platform. You will build a strong network and have a clearer idea of which Solutions Architect team fits you best. We’re looking for someone who is curious, enjoys applying technology to real problems, and is excited to keep learning. If that sounds like you, we’d love to hear from you! What you'll be doing: • Assist with technical engagements involving external developers. Help analyze their workloads and find ways NVIDIA’s technology stack can support them. Work under the mentorship of senior team members. • Contribute to the design and validation of scalable architectures, assisting in the development of integration plans and deployment approaches for customer and partner solutions. • Engage hands-on with technical topics—building, testing, and validating solutions that help customers get started with and scale NVIDIA technologies. • Participate in technical engagements, supporting customers as they solve issues and learn to navigate NVIDIA’s tools, SDKs, and platforms effectively. • Support technical enablement and platform adoption efforts, contributing to onboarding materials, demos, and documentation that help developers and enterprises integrate NVIDIA technologies. • Collaborate with engineering and product teams to understand NVIDIA’s solutions and contribute to successful customer deployments. What we need to see: • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field — recent graduate or completing degree by program start date (or equivalent experience). • Hands-on experience (academic projects or internships) with systems engineering, software development, or technical problem-solving. • Foundational knowledge in one or more of the following: GPU computing, AI/ML frameworks (PyTorch, JAX), cloud infrastructure (AWS, Azure, GCP), distributed systems, or systems-level programming (CUDA, C++, Python) — and genuine curiosity to go deeper across the stack. • Experience working with LLMs, agentic workflows, and AI application development. • Ability to explain technical concepts clearly and adapt your communication to the audience — whether that's a fellow engineer or a non-technical customer. • Strong debugging instincts, intellectual integrity when you don't know something, and drive to figure it out. • A collaborative attitude — you've worked on a team, asked for help when needed, and made others around you better. Ways to stand out from the crowd: • A hands-on technical problem solver who can clearly articulate how technology works and apply that understanding to real customer challenges. • Early experience supporting customers or partners in adopting new technologies or platforms, with a passion for enabling others to succeed. • Understanding of high‑performance networking technologies (e.g., RDMA, congestion control, high‑bandwidth interconnects) and their role in distributed AI workloads. • Familiarity with NVIDIA system software stacks: CUDA, NCCL, NVSwitch/NVLink, driver behavior, and performance tuning. • Linux, networking, security, or distributed systems background as well as practical knowledge of Git, containers, cloud-native development practices, and scheduling tools such as Docker, Kubernetes, SLURM, Ansible. • Familiarity with AI platforms, large-scale GPU clusters, HPC systems, networking, storage, or DevOps/MLOps practices. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 108,000 USD - 178,250 USD for Level 1, and 124,000 USD - 195,500 USD for Level 2. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until September 8, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

Must-haves

Assist with technical engagements involving external developers. Help analyze their workloads and find ways NVIDIA’s technology stack can support them. Work under the mentorship of senior team members.
Contribute to the design and validation of scalable architectures, assisting in the development of integration plans and deployment approaches for customer and partner solutions.
Engage hands-on with technical topics—building, testing, and validating solutions that help customers get started with and scale NVIDIA technologies.
Participate in technical engagements, supporting customers as they solve issues and learn to navigate NVIDIA’s tools, SDKs, and platforms effectively.
Support technical enablement and platform adoption efforts, contributing to onboarding materials, demos, and documentation that help developers and enterprises integrate NVIDIA technologies.
Collaborate with engineering and product teams to understand NVIDIA’s solutions and contribute to successful customer deployments.
Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field — recent graduate or completing degree by program start date (or equivalent experience).
Hands-on experience (academic projects or internships) with systems engineering, software development, or technical problem-solving.
Experience working with LLMs, agentic workflows, and AI application development.
Ability to explain technical concepts clearly and adapt your communication to the audience — whether that's a fellow engineer or a non-technical customer.
Strong debugging instincts, intellectual integrity when you don't know something, and drive to figure it out.
A collaborative attitude — you've worked on a team, asked for help when needed, and made others around you better.
A hands-on technical problem solver who can clearly articulate how technology works and apply that understanding to real customer challenges.
Early experience supporting customers or partners in adopting new technologies or platforms, with a passion for enabling others to succeed.
Understanding of high‑performance networking technologies (e.g., RDMA, congestion control, high‑bandwidth interconnects) and their role in distributed AI workloads.
Familiarity with NVIDIA system software stacks: CUDA, NCCL, NVSwitch/NVLink, driver behavior, and performance tuning.
Linux, networking, security, or distributed systems background as well as practical knowledge of Git, containers, cloud-native development practices, and scheduling tools such as Docker, Kubernetes, SLURM, Ansible.
Familiarity with AI platforms, large-scale GPU clusters, HPC systems, networking, storage, or DevOps/MLOps practices.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until September 8, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

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