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.
#NALASAHiring
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
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, or PhD in Electrical Engineering, Computer Engineering, Computer Science, Physics, Mathematics, another engineering field, or equivalent experience
- 6 or more years of solution engineering, sales engineering, cloud engineering, solution architecture, or similar experience
- Direct experience working with partners and customers
- Experience crafting and deploying large-scale cluster environments
- Hands-on experience designing, developing, and delivering distributed cloud architectures
- Strong programming, optimization, and software design fundamentals, especially in Python
- Experience with deep learning frameworks such as PyTorch and TensorFlow
- Practical expertise fine-tuning and deploying models
- Experience integrating software application stacks, libraries, and frameworks for GPU platforms
- Ability to lead complex multidisciplinary technical engagements across the customer lifecycle and cross-functional teams
- Strong time management, presentation, communication, and collaboration skills
- Self-starter mindset, continuous learning, and willingness to share insights
- Practical experience with NVIDIA GPUs, software libraries, frameworks, and foundation models
- Hands-on expertise with scaled AI cloud environments such as AWS, Azure, or GCP, plus on-premises or hybrid infrastructure
- Familiarity with NVIDIA hardware, networking, storage, and systems technologies such as NCCL, DCGM, UFM, Mission Control, or Base Command Manager
- Experience with large-scale AI model training and deployment, performance testing, benchmarking, fine-tuning, MLOps, cluster orchestration, SLURM, Kubernetes, load balancing, or cloud architecture
- 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 — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
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.”
