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Nvidia Engineering Jobs in California (NOW HIRING)

Nvidia

Senior Developer Technology Engineer

Santa Clara, CA · Hybrid

$64 - $84.50/hr

... Engineering team is a global network of world-class experts revolutionizing industries through accelerated computing. We empower developers with groundbreaking solutions that solidify NVIDIA ...

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Nvidia Engineering information

See California salary details

$45.9K

$144.9K

$171.7K

How much do nvidia engineering jobs pay per year?

As of Aug 8, 2026, the average yearly pay for nvidia engineering in California is $144,945.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $170,700.00 per year, depending on experience, location, and employer.

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

To thrive in Nvidia Engineering, candidates typically need strong proficiency in computer engineering, software development, and a solid understanding of hardware architecture, often backed by a relevant degree such as Electrical Engineering or Computer Science. Familiarity with tools like CUDA, C/C++, Python, and version control systems, as well as experience with GPU programming, are highly valued, and certifications such as Nvidia's Deep Learning Institute credentials can enhance a candidate's profile. Excellent problem-solving, team collaboration, and communication skills set top performers apart in this role. These skills and qualifications enable engineers to contribute effectively to complex, innovative projects that drive Nvidia's technological advancements.

What is an Nvidia engineer?

An Nvidia Engineering job involves designing, developing, and optimizing hardware or software solutions in areas such as graphics processing, AI, and high-performance computing. Engineers at Nvidia work on cutting-edge technologies, including GPUs, deep learning frameworks, and system architecture. Roles vary from hardware design and verification to software development and AI research, depending on expertise. Strong skills in programming, computer architecture, and problem-solving are typically required.

What types of projects do Nvidia engineers typically work on, and how is teamwork structured within the engineering department?

Nvidia Engineers commonly engage in projects related to GPU development, AI and deep learning solutions, software driver optimization, and next-generation hardware innovation. Project teams are often multidisciplinary, bringing together software, hardware, and systems engineers to collaborate closely on end-to-end product development. Engineers frequently work in agile, fast-paced environments, attend regular team stand-ups, and participate in cross-functional meetings. This collaborative structure fosters creativity, accelerates problem-solving, and ensures high-quality product delivery while offering team members exposure to diverse technologies and career growth opportunities.

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 Nvidia Engineering jobs in California? For Nvidia Engineering jobs in California, the most frequently searched job titles are:
What job categories do people searching Nvidia Engineering jobs in California look for? The top searched job categories for Nvidia Engineering jobs in California are:
What cities in California are hiring for Nvidia Engineering jobs? Cities in California with the most Nvidia Engineering job openings:
Nvidia Engineering jobs near you
Infographic showing various Nvidia Engineering job openings in California as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $144,945 per year, or $69.7 per hour.

Senior Solutions Architect, Generative AI

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

Re-posted 2 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 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

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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

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