NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. 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.
NVIDIA is seeking an experienced Solutions Architect to be a trusted technical advisor, bridging design to deployment of large-scale AI / HPC GPU infrastructure. Drive offtake and consumption by integrating libraries, frameworks, models, and software applications. Deliver GenAI, AI, and ML hardware/software to production with the most consequential customers and partners, supporting partners building next-gen GPU platforms. Own end-to-end technology solution integration with strategic customers and offer product strategy recommendations based on feedback. Profiles should be comfortable in a dynamic environment with experience in Deep Learning, LLMs, and GPU technologies. This role is an excellent opportunity to work in an interdisciplinary team at NVIDIA!
What you'll be doing:
Collaborate with NVIDIA Cloud Partners to create, implement, and deliver on NVIDIA's innovative hardware and software solutions.
Partner with SAs, Account Managers, Engineering, Product, and business leaders to align on strategies, assess technical needs, secure business opportunities for NVIDIA.
Become the primary technical driver for customers during the design, development, construction, integration, and production of GPU Cloud infrastructure and applications throughout the entire customer lifecycle.
Conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions.
Work closely with customers to build and adopt NVIDIA solutions including PoCs to address critical business needs covering infrastructure, libraries, and applications.
Prepare and deliver technical content to customers including presentations, workshops, reference architectures, tutorials, publications.
Up to 40% travel may be required.
What we need to see:
BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, Mathematics, or other Engineering fields or equivalent experience.
6+ years of Solution Engineering (or similar Sales Engineering, Cloud Engineering, Solution Architecture) including experience working directly with partners and customers.
Experience crafting and deploying large-scale cluster environments, hands-on experience designing, developing, delivering distributed Cloud architectures.
Strong fundamentals in programming, optimizations and software design, especially in Python and Deep Learning frameworks such as PyTorch and TensorFlow.
Practical expertise fine tuning and deploying models, integrating software application stacks, libraries, and frameworks to drive consumption from GPU platforms.
Motivation and skills to own and drive complex multi-disciplinary technical engagements with customers throughout the full customer lifecycle and cross-functional teams.
Efficient time management and capable of balancing multiple tasks. Excellent presentation, communication and collaboration skills.
Self-starter with a passion for growth, continuous learning, and sharing insights.
Ways to stand out from the crowd:
Practical experience with NVIDIA GPUs, software libraries, frameworks, and foundation models, such as NVIDIA Nemotron, NVIDIA NeMo Framework, NVIDIA Dynamo, NeMo Retriever, NVIDIA Triton Inference Server, TensorRT, TensorRT-LLM, NVIDIA CUDA-X
Hands-on expertise with scaled AI cloud environments (e.g., AWS, Azure, GCP) and on-premises / hybrid infrastructure, in particular inference and training workloads.
Familiarity with NVIDIA hardware (such as GPUs, networking, storage) and systems technology such as NCCL, DCGM, UFM, Mission Control, Base Command Manager.
Proficiency with large-scale AI model training / deployment encompassing GPU systems, performance testing, AI benchmarking, fine tuning, strong focus on MLOps and cluster orchestration (SLURM, K8s, orchestrator, load balancing, cloud architecture).
Experience working with enterprise developers and strong customer-facing skills.
You will also be eligible for equity and benefits.
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.Skills Required
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, Mathematics, or equivalent experience
- 6+ years in Solution Engineering, Sales Engineering, Cloud Engineering, or Solution Architecture working with partners/customers
- Experience crafting and deploying large-scale cluster environments and distributed cloud architectures
- Strong programming fundamentals and software design, especially Python and deep learning frameworks (PyTorch, TensorFlow)
- Practical expertise fine-tuning and deploying models and integrating software application stacks, libraries, and frameworks
- Proven ability to own and drive complex multidisciplinary technical engagements across customer lifecycles and cross-functional teams
- Excellent presentation, communication, collaboration, and time-management skills
- Hands-on experience with NVIDIA GPUs and NVIDIA software libraries and tools (NeMo, Triton, TensorRT, CUDA-X, Nemotron, Dynamo, NeMo Retriever, TensorRT-LLM)
- Experience with scaled AI cloud environments (AWS, Azure, GCP) and on-premises or hybrid infrastructure for training and inference workloads
- Familiarity with NVIDIA systems technologies (NCCL, DCGM, UFM, Mission Control, Base Command Manager)
- Proficiency with large-scale model training/deployment, performance testing, benchmarking, MLOps, and cluster orchestration (SLURM, Kubernetes)
- Experience working with enterprise developers and strong customer-facing skills
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
