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Remote Nvidia Engineering Jobs in California (NOW HIRING)

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 ...

CUDA Kernel Engineer (Remote US)

San Francisco, CA · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

Remote US Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on ... engineering best practices. What Were Looking For * Proven track record building NVIDIA CUDA ...

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Remote Nvidia Engineering information

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.

What are the most commonly searched types of Nvidia Engineering jobs in California? The most popular types of Nvidia Engineering jobs in California are:
What are popular job titles related to Remote Nvidia Engineering jobs in California? For Remote Nvidia Engineering jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Nvidia Engineering jobs in California look for? The top searched job categories for Remote Nvidia Engineering jobs in California are:
What cities in California are hiring for Remote Nvidia Engineering jobs? Cities in California with the most Remote Nvidia Engineering job openings:
Infographic showing various Remote Nvidia Engineering job openings in California as of August 2026, with employment types broken down into 88% Full Time, 6% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Senior Solutions Architect, Generative AI

Nvidia

Santa Clara, CA • On-site, Remote

Full-time

Re-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

7th of 244 rated software companies


Job description

NVIDIA is looking for an AI Solutions Architect with deep, hands-on experience in large-scale GPU systems. This role involves working with some of the world's leading consumer internet companies and frontier labs building foundation models. Primary responsibilities include accelerating customer workloads, designing high-performance AI infrastructure, and leading technical engagements around NVIDIA technologies. We work with the world's most successful technology companies, uniquely positioning you to observe and influence emerging infrastructure trends using the latest advancements. Join us in this exciting endeavor!

What You'll Be Doing:

  • Collaborating closely with customers to maximize GPU utilization and end-to-end workload throughput while improving infrastructure reliability and reducing infrastructure costs.

  • Designing and optimizing large-scale AI clusters across GPU compute, high-performance networking, storage, workload scheduling, orchestration, and observability.

  • Profiling distributed training and inference workloads to identify bottlenecks across GPUs, CPUs, memory, network fabrics, storage systems, and software stack.

  • Diagnosing complex infrastructure and distributed systems issues spanning InfiniBand and RoCE fabrics, cloud interconnects, RDMA, NCCL, NVLink, and NVSwitch.

  • Leading proof-of-concepts and performance studies for large-scale AI infrastructure, developing benchmarking tools, automation, runbooks, and technical collateral as needed.

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

What We Need To See:

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

  • 6+ years of experience in AI infrastructure, systems engineering, high-performance computing, networking, site reliability engineering, or a related technical role.

  • Deep understanding of Linux systems, distributed computing, GPU architectures, and the hardware and software components of large-scale AI clusters.

  • Hands-on experience designing, deploying, operating, or troubleshooting high-performance GPU networks in on-premises or cloud environments using technologies such as InfiniBand, RoCE, or GPUDirect RDMA.

  • Experience debugging NCCL communication and distributed collective performance, including topology, transport, congestion, routing, and host-level configuration issues.

  • Experience profiling AI workloads and identifying performance bottlenecks across compute, networking, storage, and orchestration layers.

  • Experience with cluster schedulers and orchestration platforms such as Kubernetes and Slurm, along with containers and production monitoring systems.

  • Proficiency with Python, shell scripting, or similar languages for infrastructure automation, benchmarking, and systems troubleshooting.

Ways To Stand Out From The Crowd:

  • Experience architecting and operating large-scale production GPU clusters for distributed training or inference.

  • Deep expertise with NVIDIA infrastructure technologies such as DGX/HGX systems, NVLink, NVSwitch, NCCL, InfiniBand, and Spectrum-X.

  • Hands-on experience using tools and telemetry such as NCCL tests, DCGM, Nsight Systems, fabric counters, and host- or switch-level diagnostics to isolate performance and reliability issues.

  • Understanding of network topology, congestion control, collective communication patterns, and their impact on distributed AI workload performance.

  • Experience optimizing storage and data pipelines to sustain high-throughput training and inference workloads.

We make extensive use of conferencing tools, but occasional travel (20%) 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!

With competitive salaries and a generous benefits package, NVIDIA is recognized as one of the technology world's most sought-after employers. This role offers a chance to make a broad impact at NVIDIA by advancing innovation with our consumer internet & frontier labs partners. Are you inventive, diligent, committed, and driven? Do you enjoy tackling challenges? If so, we want to hear from you!

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 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 3, 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

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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