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Remote Nvidia Engineering Jobs (NOW HIRING)

... NVIDIA's solutions. Provide primarily onsite technical support, with remote and travel-based ... What we need to see: BS or MS in Engineering, Electrical Engineering, Physics, or Computer Science ...

Senior Software Engineer - Topography

$125K - $165K/yr

Strong production engineering experience in Go or another systems language. Experience with ... NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High ...

Senior Software Engineer - Topography

$125K - $165K/yr

Strong production engineering experience in Go or another systems language. * Experience with ... NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High ...

... NVIDIA's solutions. Provide primarily onsite technical support, with remote and travel-based ... What we need to see: BS or MS in Engineering, Electrical Engineering, Physics, or Computer Science ...

$135K - $181K/yr

NVIDIA Dynamo is a high-throughput, low-latency inference framework for serving generative AI and ... Deep understanding of memory hierarchies (GPU HBM, host DRAM, SSD, and remote/object storage) and ...

Showing results 21-40

Remote Nvidia Engineering information

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$57K

$137K

$197K

How much do remote nvidia engineering jobs pay per year?

As of Sep 2, 2026, the average yearly pay for remote nvidia engineering in the United States is $137,006.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,500.00 and $151,500.00 per year, depending on experience, location, and employer.

What is a remote Nvidia engineer?

A Remote Nvidia Engineer is a professional who works for Nvidia, or with Nvidia technologies, from a location outside of a traditional office setting. These engineers may specialize in areas such as GPU development, AI research, software engineering, or hardware design, and they collaborate with teams virtually. Remote Nvidia Engineers use digital tools to communicate, manage projects, and contribute to cutting-edge technologies in graphics processing, artificial intelligence, and computing platforms. The remote aspect allows for flexible work arrangements and the ability to participate in global projects.

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

To excel as a Remote Nvidia Engineer, you typically need a strong background in computer engineering, programming (e.g., C++, Python), and experience with GPU architectures, often supported by a relevant degree. Familiarity with Nvidia tools like CUDA, cuDNN, and deep learning frameworks, as well as proficiency in remote collaboration platforms, are crucial. Strong problem-solving skills, self-motivation, and effective communication are vital soft skills for working independently and collaborating across distributed teams. These competencies ensure efficient development, troubleshooting, and innovation in Nvidia's complex, high-performance computing environments.

What are some common challenges faced by engineers working remotely for Nvidia, and how can they be overcome?

Remote engineers at Nvidia often encounter challenges related to communication across time zones, staying aligned with fast-paced project developments, and maintaining visibility within distributed teams. To overcome these, it's important to proactively engage in virtual meetings, leverage collaboration tools like Slack and Jira, and regularly update your team on progress. Building strong relationships with peers and seeking out mentorship opportunities can also help remote engineers stay connected and advance within the company.

What is the difference between Remote Nvidia Engineering vs Remote Nvidia Data Scientist?

AspectRemote Nvidia EngineeringRemote Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU programmingBachelor's or higher in Data Science, Statistics, or related; proficiency in machine learning and data analysis
Work EnvironmentDesign, develop, and optimize GPU hardware/software; collaborative teamsAnalyze large datasets, develop models, and generate insights; often cross-functional teams
Employer & Industry UsagePrimarily in hardware, AI, and high-performance computing sectorsPrimarily in AI, analytics, and research sectors

Remote Nvidia Engineering focuses on hardware and software development for GPUs, requiring engineering credentials and technical skills. Remote Nvidia Data Scientists analyze data and build models, requiring expertise in data science. Both roles are remote, but they serve different functions within Nvidia's ecosystem.

More about Remote Nvidia Engineering jobs

What cities are hiring for Remote Nvidia Engineering jobs?

Cities with the most Remote Nvidia Engineering job openings:

What are the most commonly searched types of Nvidia Engineering jobs?

The most popular types of Nvidia Engineering jobs are:

What states have the most Remote Nvidia Engineering jobs?

States with the most job openings for Remote Nvidia Engineering jobs include:

Infographic showing various Remote Nvidia Engineering job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, and 5% Contract. Highlights an 100% Remote job distribution, with an average salary of $137,006 per year, or $65.9 per hour.

Senior Customer Success Engineer - DGX Cloud

Nvidia

Santa Clara, CA • Remote

$65 - $83.75/hr

Full-time

Re-posted 5 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

The DGX Cloud organization bridges customer success and cloud infrastructure engineering, partnering directly with NVIDIA's internal research and product teams to accelerate AI workload development. As a Customer Success Engineer, you'll embed deeply with internal customers - gaining a thorough understanding of their applications and translating that knowledge into architectural guidance, best practices, and hands-on solutions. This role sits at the unique intersection of solutions architecture and platform strategy: you'll write code, build tooling, and help shape NVIDIA's GPU capacity management from the inside.

Working across Engineering, Product, Finance, and Operations, you'll connect infrastructure roadmaps to business needs in a way that directly influences how NVIDIA's most advanced AI teams move faster. If you thrive where deep technical work meets high-stakes collaboration, this role was built for you. What you'll be doing: Design and implement distributed cloud infrastructure at scale - spanning compute, storage, networking, and GPU capacity management across IaaS, PaaS, and SaaS models zendesk Partner with internal research and product teams to understand workloads from both a technology and business perspective, providing architectural guidance that drives their success Contribute code directly when needed to move projects forward, and codify working patterns into tools, playbooks, and building blocks that others can reuse Build and maintain agentic tooling to automate operational workflows and infrastructure resource management Analyze the DGX Cloud ecosystem to understand current customer demand and future capacity needs, driving infrastructure efficiency initiatives in partnership with Engineering, Finance, and Product Present technical roadmaps, architecture decisions, and demos to internal stakeholders and NVIDIA leadership, driving cross-functional consensus on infrastructure strategy What we need to see: BS or MS in Computer Science, Engineering, or a related field, or equivalent experience.

12+ years of experience designing and building distributed systems and cloud infrastructure, with demonstrated experience in GPU capacity management for high-performance computing Demonstrated ability to write production code in Golang, Java, C, C++, Python, or Rust Experience with Kubernetes and/or distributed task scheduling Strong background in Infrastructure, Networking, Storage, and DevOps scripting/tooling Experience deploying AI/ML workloads at scale Strong communication and relationship-building skills, with a demonstrated ability to drive cross-functional consensus and align stakeholders across departments NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.

NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us.

#LI-Remote Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 14, 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