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Remote Nvidia Hardware Engineer Jobs (NOW HIRING)

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 ...

Do you want to be part of the team that brings GenAI, AI, ML, etc. hardware and software ... What we need to see: * BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or ...

Senior Software Engineer - Topography

Santa Clara, CA · Remote

$143K - $189K/yr

... edge NVIDIA hardware to ensure GPU to GPU communication is optimized for large-scale workloads ... If you're a creative, curious, and driven technical leader, we want to hear from you! #LI-Remote ...

Senior Software Engineer - Topography

$125K - $165K/yr

... edge NVIDIA hardware to ensure GPU to GPU communication is optimized for large-scale workloads ... If you're a creative, curious, and driven technical leader, we want to hear from you! #LI-Remote ...

New

$104K - $143K/yr

We ensure that key deep learning frameworks run optimally on NVIDIA hardware, enabling developers and researchers to push the boundaries of what's possible in AI. What you'll be doing: Join a team of ...

$94K - $130K/yr

Senior Hardware Engineer - Remote Curtiss-Wright is seeking an experienced Senior Hardware Engineer to join our Defense Solutions Group. This role involves designing and developing complex electrical ...

Hardware Engineer, Senior

Orlando, FL · On-site +1

$135K - $165K/yr

Overview The Hardware Engineer provides engineering support for the design, drafting, development ... THIS HYBRID POSITION REQUIRES 3 DAYS OF WORK IN THE OFFICE AND 2 DAYS REMOTE PER WEEK ...

At NVIDIA, we believe that inference will be driving increasing amount of compute, and as the hardware becomes more capable, it is crucial to make it easy for users to get the best performance as ...

... NVIDIA's hardware architecture. This means designing and building things like new abstractions ... Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries ...

$122K - $161K/yr

... NVIDIA's hardware architecture. This means designing and building things like new abstractions ... Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries ...

Senior Software Engineer, Matrix Multiplication

OR · On-site +1

$122K - $161K/yr

... NVIDIA's hardware architecture. This means designing and building things like new abstractions ... Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries ...

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Remote Nvidia Hardware Engineer information

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$51K

$146.2K

$196.5K

How much do remote nvidia hardware engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote nvidia hardware engineer in the United States is $146,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,500.00 and $163,000.00 per year, depending on experience, location, and employer.

What does a remote Nvidia hardware engineer do?

A Remote Nvidia Hardware Engineer focuses on designing, developing, and testing hardware components and systems for Nvidia products, such as graphics processing units (GPUs) and related technologies, while working from a remote location. They collaborate with cross-functional teams to ensure hardware solutions meet performance, reliability, and efficiency standards. Their work may include circuit design, board layout, hardware debugging, and supporting the integration of Nvidia hardware into various devices. Remote engineers use digital communication and collaboration tools to work effectively with global teams and contribute to innovative hardware solutions.

What are the key skills and qualifications needed to thrive as a remote Nvidia hardware engineer, and why are they important?

To thrive as a Remote Nvidia Hardware Engineer, you need a strong background in electrical or computer engineering, experience with GPU architecture, and proficiency in hardware design and validation. Expertise with tools such as Verilog/VHDL, simulation environments, and familiarity with Nvidia’s development platforms or relevant certifications is common. Strong problem-solving abilities, effective remote communication, and collaborative teamwork skills set top candidates apart. These competencies ensure efficient development, troubleshooting, and innovation in high-performance hardware solutions within distributed teams.

What are some common challenges faced by remote Nvidia hardware engineers, and how can they be addressed?

Remote Nvidia Hardware Engineers often encounter challenges related to effective collaboration and communication, especially when working on complex hardware design and testing with distributed teams. Staying aligned with project milestones, ensuring access to necessary hardware resources, and troubleshooting remotely can also be demanding. These challenges can be addressed by leveraging robust collaboration tools, maintaining clear documentation, and scheduling regular virtual meetings to synchronize efforts. Additionally, using remote desktop solutions and cloud-based simulation environments can help bridge the gap when physical access to hardware is limited.

What is the difference between Remote Nvidia Hardware Engineer vs Remote Nvidia Software Engineer?

AspectRemote Nvidia Hardware EngineerRemote Nvidia Software Engineer
Required CredentialsBachelor's or higher in Electrical Engineering, Computer Engineering, or related; hardware design certificationsBachelor's or higher in Computer Science, Software Engineering, or related; programming certifications
Work EnvironmentDesigning and testing hardware components, collaborating with hardware teamsDeveloping software, drivers, and algorithms for Nvidia products
Industry UsageHardware development for GPUs, AI accelerators, and embedded systemsSoftware development for drivers, SDKs, and AI frameworks

The main difference is that Remote Nvidia Hardware Engineers focus on designing and testing physical hardware components, while Remote Nvidia Software Engineers develop the software that runs on Nvidia hardware. Both roles require technical expertise but differ in their focus areas within the Nvidia ecosystem.

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Infographic showing various Remote Nvidia Hardware Engineer job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $146,230 per year, or $70.3 per hour.

Senior Solutions Architect, NVIDIA Cloud Partners

Nvidia

New York, NY • On-site, Remote

$69.50 - $95.25/hr

Full-time

Re-posted 13 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies


Job description

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!

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.

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.

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.

We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

#NALASAHiring

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 August 1, 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.

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About Nvidia

Sourced by ZipRecruiter

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.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993