2

Remote Nvidia Engineering Jobs (NOW HIRING)

NVIDIA defines and delivers the computing infrastructure of today and tomorrow. We are committed ... Recruit & manage a team of solutions architects, system/network and software engineers focused on ...

Solutions Architect, Agentic Optimization

$64.50 - $85/hr

Partnering with NVIDIA's software engineering, product, and sales teams to secure design wins and ... We are open to remote work. We look forward to having you join our team! Your base salary will be ...

NVIDIA defines and delivers the computing infrastructure of today and tomorrow. We are committed ... Recruit & manage a team of solutions architects, system/network and software engineers focused on ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

Solutions Architect, Agentic Optimization

$64.50 - $85/hr

Partnering with NVIDIA's software engineering, product, and sales teams to secure design wins and ... We are open to remote work. We look forward to having you join our team. Your base salary will be ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

Showing results 41-60

Remote Nvidia Engineering information

See salary details

$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.

Manager, First Time Deployment - NVIS

Nvidia

OR • On-site, Remote

Full-time

Re-posted 20 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

Will you be part of the team that helps our partners to develop customer solutions using the latest NVIDIA full stack accelerated computing platform. NVIDIA defines and delivers the computing infrastructure of today and tomorrow. We are committed that these infrastructures deliver the highest value to our customers who own and operate these infrastructures.

We are looking for a team leader to operationalize the latest technologies at NVIDIA by bridging the gap between prototype models and production-ready deployment plans. The team will drive initial deployment setup, prepares sites, establishes product feedback loops to design engineering teams, assembles validation data, resolves obstacles, applies workarounds, and details deployment plans. They lead all aspects of making the latest NVIDIA products and systems functional by capturing install and bring-up evidence, handle the validation process, describe blockers, and find solutions to deploy AI Factories globally.

What you will be doing: Recruit & manage a team of solutions architects, system/network and software engineers focused on large-scale GPU and AI networking deployments. Set priorities, allocate resources, mentor, and ensure high-quality customer delivery across multiple concurrent projects - while remaining directly involved in key technical reviews, design decisions, and critical debug efforts. Provide deep subject-matter expertise in advanced GPU and network systems and serve as the senior technical point of contact for strategic customers.

Personally lead and guide complex compute/network configuration and performance debugging, working side-by-side with your team to deliver performant, reliable clusters. Guide your team as they lead network / compute / software architecture discussions, and support server, network, and cluster bring-up, including on-site data center work where needed. Systematically collect and synthesize customer-specific requirements across your portfolio.

Partner with GPU/Network Systems Engineering, Product Management, and Sales to influence roadmap priorities and packaging of reference designs and solutions. Demonstrate SME in advanced GPU & network systems and be a trusted technical advisor to NVIDIA's strategic customers. Bring customer-specific requirements to product teams to guide product roadmap features.

Identify new project opportunities for NVIDIA products and technology solutions in data center and AI applications. Work closely with the GPU/Network Systems Engineering, Product management and Sales teams What we need to see: BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience. 8+ overall years in Systems/Solutions/Field Engineering, Network or Data Center Engineering, or similar roles, with 2+ years leading or mentoring engineers or architects (formal manager or strong tech lead).

System-level expertise across CPU/GPU server architecture, NICs, Linux, system software, and kernel drivers. Experience with data center networking (Ethernet and/or InfiniBand switches, fabrics, and associated tooling) and familiarity with data center infrastructure (power, cooling, deployment constraints). Proven ability to lead technical teams, set priorities, and drive complex projects from design through production.

Demonstrated success working with Product Management, Sales, and Engineering. Strong time management skills and ability to balance planning with hands-on support where needed. Excellent written and verbal communication, including the ability to lead customer meetings, communicate status and risks, and produce clear design docs, debug summaries, and presentations.

Ways to stand out from the crowd: Direct people management & recruiting experience for geographically distributed technical teams. Track record leading bring-up and deployment of large clusters or supercomputing environments. Background in external customer-facing roles (field engineering, escalations, or pre/post-sales architecture).

Systems engineering, coding, and debugging skills including experience with C/C++, Linux kernel and drivers Hands-on experience with NVIDIA GPU systems and SDKs (e.g., CUDA), NVIDIA networking technologies (NICs, RoCE, InfiniBand), and/or ARM-based CPU solutions as well as familiarity with virtualization and cloud-native networking concepts. We make extensive use of conferencing tools, but occasional (30%) travel is required for on-site visit to customers and industry events. We are open to remote work location and look forward to have 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 184,000 USD - 287,500 USD for Level 3, and 216,000 USD - 345,000 USD for Level 4. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 18, 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


Nvidia logo

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