1

Contract Software Engineer Gpu Jobs in California

GPU Software Engineer

San Diego, CA · On-site

$98K - $148K/yr

Qualcomm Graphics Software Engineers architect, design, implement, verify, and optimize the structure and performance of GPU hardware, drivers, features, applications, and tools. Qualcomm Engineers ...

Senior GPU Software Engineer

San Diego, CA · On-site

$130K - $171K/yr

Qualcomm Graphics Software Engineers architect, design, implement, verify, and optimize the structure and performance of GPU hardware, drivers, features, applications, and tools. Qualcomm Engineers ...

Senior Firmware Engineer - GPU

Santa Clara, CA · On-site

$140K - $185K/yr

We are searching for an outstanding software engineer to fill an exciting, yet fun role on our GPU Firmware team. You will be joining a team whose primary mission is solving the intricate enigma of ...

Software Engineer

San Jose, CA · On-site

$60 - $70/hr

Protingent Staffing has an exciting contract Software Engineerwith our client located in San Jose, CA. * We're looking for a junior software engineer who can help build production applications ...

Senior Firmware Engineer - GPU

Santa Clara, CA · On-site

$140K - $185K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... We're looking for an experienced System Software Engineer to help develop the boot, firmware, and ...

Showing results 41-60

Contract Software Engineer Gpu information

What is the difference between Contract Software Engineer Gpu vs Contract Software Engineer Cloud?

AspectContract Software Engineer GpuContract Software Engineer Cloud
Required CredentialsProficiency in GPU programming, CUDA, OpenCLExperience with cloud platforms, APIs, and cloud-specific tools
Work EnvironmentDeveloping high-performance GPU applications, often on specialized hardwareBuilding and deploying applications on cloud infrastructure, remote environments
Employer & Industry UsageTech companies, AI, gaming, scientific computingCloud service providers, SaaS companies, enterprise solutions
Search & Comparison IntentLooking for GPU-focused software engineering rolesSeeking cloud-based software engineering opportunities

The main difference between Contract Software Engineer Gpu and Contract Software Engineer Cloud lies in their focus areas. GPU roles emphasize high-performance computing and specialized hardware, while cloud roles focus on deploying and managing applications in cloud environments. Both require strong software development skills, but their tools and work settings differ significantly.

What are the most commonly searched types of Software Engineer Gpu jobs in California?

The most popular types of Software Engineer Gpu jobs in California are:

What cities in California are hiring for Contract Software Engineer Gpu jobs?

Cities in California with the most Contract Software Engineer Gpu job openings:

Senior Systems Software Engineer - GPU Performance at Scale

Nvidia

Santa Clara, CA

Full-time

Re-posted 13 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

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.

Come join the team and see how you can make a lasting impact on the world. We are looking for a dedicated engineer for the Senior Systems Software Engineer role, focusing on GPU Performance at Scale. At NVIDIA, this role is uniquely positioned to drive innovation in AI and GPU computing.

You will contribute to world-class computing hardware and software, fueling groundbreaking advancements in artificial intelligence. You will provide insights on large-scale system composition and tuning mechanisms for high-performance compute runs. Collaborate with researchers, developers, and customers to craft improved workflows and develop new, leading solutions.

Engage with HPC, OS, CPU, GPU compute, and systems specialists to architect, build, and optimize large-scale performance platforms. What you'll be doing: Lead the implementation of performance practices in large-scale GPU infrastructure, delivering powerful tools, methodologies, and flows to validate and improve multiple datacenter products concurrently. Align next-generation AI workloads with next-generation datacenter builds for NVIDIA GPUs, CPUs, and networking hardware.

Engage early with HW/FW/SW/platform internal and customer teams. Develop engineering solutions that provide continuous insights into the performance of AI workloads in evolving environments, generating swift insights into improvements and regressions. Decompose high-complexity performance or stability issues into minimal reproduction cases, working towards identifying the root cause.

Participate in collaborations with various SW and FW teams (BMC/SBIOS/OS/drivers, etc.) to develop outstanding methods and tools. Analyze, debug, and resolve critical firmware and software issues to achieve the highest AI workload performance at scale. What we need to see: Proven understanding of accelerated computing software stacks (CUDA)

Experience with modern cloud and container-based enterprise computing architectures, with Slurm preferred. Strong programming and scripting experience in C/C++/Python/Bash. Deep expertise in systems architecture and the impact of various components on performance.

Experience with container technology and Linux-based OSes, with Docker preferred. Experience supporting high-performance computing or deep learning in engineering or academic research communities. Strong teamwork and communication skills, coupled with results-focused analytical abilities.

BS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience); MS or PhD desirable with 8+ years of applicable experience. Ways to Stand Out From the Crowd End-to-end GPU performance engineering from the profiler to systems analysis. Linux systems programming and optimization experience.

Exposure to virtualization techniques and cloud platform solutions. Experience with scheduling and resource management systems. Experience with large-scale HPC environments.

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 September 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

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