Cloud Solutions Engineer Jobs at NVIDIA with Visa Sponsorship
Cloud Solutions Engineer roles at NVIDIA sit at the intersection of deep technical expertise and client-facing advisory work, requiring fluency in GPU-accelerated infrastructure, cloud platforms, and enterprise sales cycles. NVIDIA has a consistent track record of sponsoring international engineers in this function across H-1B, E-3, and Green Card pathways.
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INTRODUCTION
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 outtake 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!
ROLE AND RESPONSIBILITIES
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.
BASIC QUALIFICATIONS
What we need to see:
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, Mathematics, or other Engineering fields or equivalent experience.
- 10+ 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.
PREFERRED QUALIFICATIONS
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.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 5, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.

INTRODUCTION
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 outtake 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!
ROLE AND RESPONSIBILITIES
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.
BASIC QUALIFICATIONS
What we need to see:
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, Mathematics, or other Engineering fields or equivalent experience.
- 10+ 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.
PREFERRED QUALIFICATIONS
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.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 5, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
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Get Access To All JobsTips for Finding Cloud Solutions Engineer Jobs at NVIDIA Jobs
Align your credentials to NVIDIA's specialty occupation standard
NVIDIA's H-1B filings for Cloud Solutions Engineers require a degree in computer science, electrical engineering, or a closely related field. A general IT or business degree rarely satisfies the specialty occupation threshold USCIS applies to this role.
Target NVIDIA's solutions engineering pipeline directly
NVIDIA recruits Cloud Solutions Engineers through both its enterprise sales org and its developer relations teams. Identifying which business unit owns the open role shapes how you frame your background, since GPU infrastructure experience reads differently to each hiring team.
Prepare for a multi-stage technical screen before sponsorship conversations
NVIDIA's interview process for this role typically includes a system design round and a live customer scenario exercise. Clearing the technical bar before any sponsorship discussion means your immigration timeline doesn't become a negotiating variable during the offer stage.
Understand how E-3 eligibility changes your application timeline
If you're an Australian citizen, the E-3 visa bypasses the H-1B lottery entirely. NVIDIA sponsors E-3s for this role, so you can start a consular appointment process as soon as your offer letter and Labor Condition Application are ready, without waiting for an October 1 start date.
Confirm your LCA wage level matches your offered compensation
DOL requires NVIDIA to file a Labor Condition Application certifying your salary meets the prevailing wage for a Cloud Solutions Engineer in your work location. Mismatches between the LCA wage level and your offer can delay or complicate the I-129 filing.
Use Migrate Mate to find open Cloud Solutions Engineer roles at NVIDIA
Filtering for visa-sponsoring employers in this specific function saves significant time. Migrate Mate surfaces Cloud Solutions Engineer openings at companies with active sponsorship track records, so you're applying where sponsorship is already an established practice.
Cloud Solutions Engineer at NVIDIA jobs are hiring across the US. Find yours.
Find Cloud Solutions Engineer at NVIDIA JobsFrequently Asked Questions
Does NVIDIA sponsor H-1B visas for Cloud Solutions Engineers?
Yes, NVIDIA sponsors H-1B visas for Cloud Solutions Engineers. The role qualifies as a specialty occupation under USCIS standards because it requires at minimum a bachelor's degree in a field like computer science or electrical engineering. NVIDIA handles the I-129 petition and associated Labor Condition Application filing through its immigration team, typically working with outside counsel once an offer is extended.
How do I apply for Cloud Solutions Engineer jobs at NVIDIA?
Apply directly through NVIDIA's careers site or find open roles through Migrate Mate, which filters for visa-sponsoring employers in this function. Cloud Solutions Engineer positions at NVIDIA typically require demonstrated experience with cloud platforms such as AWS, Azure, or GCP, plus familiarity with GPU computing or accelerated infrastructure. Tailoring your resume to the specific business unit posting, whether enterprise sales or developer relations, increases your chances of clearing the initial screen.
Which visa types does NVIDIA commonly use for Cloud Solutions Engineer roles?
NVIDIA sponsors H-1B, E-3, and Green Card pathways including EB-2 and EB-3 classifications for Cloud Solutions Engineers. H-1B is the most common route for non-Australian nationals and is subject to the annual lottery. E-3 is available exclusively to Australian citizens and offers a faster, lottery-free path. Green Card sponsorship typically follows a period of employment and is initiated through the PERM labor certification process with the DOL.
What qualifications does NVIDIA expect for Cloud Solutions Engineer candidates?
NVIDIA looks for candidates with hands-on experience deploying and architecting solutions on at least one major cloud platform, alongside strong communication skills for client-facing engagements. Familiarity with NVIDIA's GPU product stack or accelerated computing concepts, such as CUDA or AI inference infrastructure, significantly strengthens an application. A bachelor's degree in computer science, engineering, or a closely related technical discipline is the baseline requirement, and advanced degrees are common among hired candidates.
How do I estimate the timeline from offer to visa approval for a Cloud Solutions Engineer role at NVIDIA?
For H-1B, count on at least six to eight months if you're starting from a lottery registration, since the cap year runs April through September and employment can't begin before October 1. E-3 applicants can move faster since there's no lottery; consular processing in Australia often takes two to six weeks from LCA certification to visa stamp. NVIDIA's immigration team typically initiates the LCA filing with DOL within days of a signed offer, which is the first formal step in either pathway.
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