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Remote Nvidia Engineering Jobs (NOW HIRING)

Nvidia

Senior Software and System Architect

Santa Clara, CA · Remote

$152K - $206K/yr

... engineer with a real passion for technology, we want to hear from you! #LI-Remote Your base salary ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Nvidia

Senior Software and System Architect

New York, NY · Remote

$141K - $192K/yr

... engineer with a real passion for technology, we want to hear from you! #LI-Remote Your base salary ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Nastech Global

AI Infra SRE Engineer

San Jose, CA · Remote

$58.25 - $77.50/hr

Remote Duration: Fulltime Must-have * NVIDIA (DGX) or equivalent high-performance-compute (HPC) clusters (e.g. Cray, HPE, IBM) * Cisco UCS C885A * Docker Good to have * DevOps Automation * CI/CD ...

Weekday AI

CUDA Engineering Expert

$80 - $100/hr

Experience optimizing kernels for NVIDIA Blackwell hardware is a plus * Familiarity with NSight ... This is a fully remote role that can be completed on your own schedule. * Projects can be extended ...

Open Select

Member of Engineering, Backend - AI

$290K/yr

Fully remote (East Coast preferred) Salary: Up to $290k + equity Industry: AI, Developer Platform ... Unmatched funding: $626M raised (Seed/Series A/B), backed by Bain Capital, Nvidia, Redpoint ...

PICTOR LABS INC

$89K - $123K/yr

... NVIDIA hardware, and ensuring our inference infrastructure meets FDA and SOC2 compliance ... Remote US Company: Pictor Labs Employment Type: Full-time Responsibilities * Design, development ...

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Remote Nvidia Engineering information

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$197K

How much do remote nvidia engineering jobs pay per year?

As of Jul 23, 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 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 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 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:
What job categories do people searching Remote Nvidia Engineering jobs look for? The top searched job categories for Remote Nvidia Engineering jobs are:
Remote Nvidia Engineering jobs near you
Infographic showing various Remote Nvidia Engineering job openings in the United States as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $137,006 per year, or $65.9 per hour.
Solutions Architect, Agentic Optimization

Solutions Architect, Agentic Optimization

Nvidia

Santa Clara, CA • On-site, Remote

$74 - $97.50/hr

Full-time

Posted 10 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

5th of 215 rated software companies

Job description

NVIDIA is looking for an AI Solutions Architect with hands-on experience in efficient AI model training and/or deployment for a customer facing role. Primary responsibilities will be to help accelerate customer workloads and lead customer technical engagements around NVIDIA software and technologies. We work with the world's most successful technology companies, and this role uniquely positions you to observe emerging industry trends at the cutting edge. Join us in this exciting endeavor!

What you'll be doing:

  • Collaborating closely with customers to improve their workload performance and reduce infrastructure costs.

  • Leading and developing proof-of-concepts for AI solutions applied to the Consumer Internet industry, including areas like LLMs and recommenders, and building collateral (notebook/code) as needed.

  • Developing and debugging software for NVIDIA and open-source AI frameworks and libraries.

  • Partnering with NVIDIA's software engineering, product, and sales teams to secure design wins and drive the development of innovative solutions based on customer feedback.

What we need to see:

  • BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields, or equivalent experience.

  • 5+ years of experience as an AI/Software Engineer with proven track record coding in Python and/or C++ with popular AI software libraries and GPUs.

  • Experience with profiling and optimizing model training/inference performance on GPUs.

  • Experience developing and optimizing GPU kernels for deep learning, with a focus on GEMM and attention kernels.

  • Strong communication skills, with the ability to clearly convey ideas and code through GitHub, documentation, and presentations.

  • A great teammate who enjoys collaborating with cross-functional teams including Engineering, Research, Sales, Product, and Marketing.

  • Self-starter with a passion for growth, continuous learning, and sharing insights with the team.

Ways to stand out from the crowd:

  • Full stack experience.

  • Experience working with enterprise developers and strong customer-facing skills.

  • Familiarity with MLOps technologies such as containers, Kubernetes, and data center deployments.

  • Experience with large-scale production data pipelines and AI model training/deployment.

  • Creative problem-solving skills for debugging and resolving complex issues.

We make extensive use of conferencing tools, but occasional travel is required for local on-site visits to customers and conferences. We are open to remote work. We look forward to having you join our team!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 17, 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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