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Software Engineer Gpu Jobs (NOW HIRING)

Cohere

Software Engineer, GPU Infrastructure (HPC)

$110K - $144K/yr

The Staff Software Engineer will build and operate GPU/TPU superclusters, collaborating closely with AI researchers to enhance infrastructure for AI workloads. Responsibilities : • Build and scale ...

Nvidia

System Software Engineer - GPU and SOC

Redmond, WA

$193K - $229K/yr

As a GPU/SOC system software engineer, you will work with a team of very dedicated software and hardware engineers involving a wide variety of technologies. As someone who is hardworking and ...

KLA

Sr. AI Software Engineer (GPU/C++)

Milpitas, CA · On-site

$139K - $184K/yr

They are seeking a Sr. AI Software Engineer with a focus on C++ and GPU to design and implement core infrastructure components that support AI/ML workloads across various frameworks and hardware ...

Nebius

Lead Software Systems Engineer - GPU Performance

$170K - $300K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

We are looking for a Lead Software Systems Engineer - GPU Performance to play a key role in building our hyperscaler platform, working across its core components while analyzing and optimizing the ...

Xoriant Corporation

GPU Software Engineer

San Jose, CA · On-site

GPU Software Engineer Location: San Jose, CA Duration: 6+ months contract (Long Term) Roles and Responsibilities: * As a GPU Software Engineer, you will be equipped to develop GPU IP from the early ...

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Software Engineer Gpu information

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$63.5K

$147.5K

$205.5K

How much do software engineer gpu jobs pay per year?

As of Aug 17, 2026, the average yearly pay for software engineer gpu in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What is a software engineer GPU?

A Software Engineer GPU is a specialist who designs, develops, and optimizes software that runs on Graphics Processing Units (GPUs). These engineers focus on maximizing the performance of applications—such as graphics rendering, machine learning, or scientific computation—by leveraging the parallel processing power of GPUs. They often work with languages like CUDA or OpenCL and collaborate with hardware teams to ensure efficient integration of software and GPU hardware. Their work is vital in industries like gaming, AI, automotive, and high-performance computing.

What are the key skills and qualifications needed to thrive as a software engineer GPU?

To thrive as a Software Engineer GPU, you need strong programming skills in C/C++, parallel computing concepts, and a solid background in computer science or related fields. Familiarity with GPU programming frameworks such as CUDA or OpenCL, version control systems, and performance profiling tools is typically required. Analytical thinking, problem-solving abilities, and effective teamwork are essential soft skills for excelling in this role. These competencies ensure the development of optimized, high-performance software that leverages GPU architectures for demanding computational tasks.

How does a software engineer GPU typically collaborate with hardware and other engineering teams?

As a Software Engineer focusing on GPU, you will frequently work closely with hardware engineers, driver developers, and performance analysts. Collaboration often involves optimizing software to leverage GPU capabilities, troubleshooting performance bottlenecks, and ensuring compatibility with evolving hardware architectures. Effective communication and cross-functional teamwork are essential, as solutions often require aligning software design with hardware constraints and roadmaps. This collaborative environment not only broadens your technical understanding but also provides opportunities to learn from diverse engineering disciplines.

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

AspectSoftware Engineer GpuSoftware Engineer
Required SkillsGPU programming, parallel computing, CUDA/OpenCLGeneral software development, algorithms, coding
Work EnvironmentHigh-performance computing, graphics, AIWeb, mobile, enterprise applications
CertificationsCUDA certifications, relevant degreesVaries widely, often general CS degrees
Industry UsageGraphics, AI, scientific computingSoftware development across industries

Software Engineer Gpu specializes in GPU-based programming for high-performance tasks, while a Software Engineer has a broader focus on general software development. Both roles require strong coding skills, but GPU engineers focus more on parallel processing and graphics technologies. The choice depends on your interest in graphics and high-performance computing versus general software development.

What cities are hiring for Software Engineer Gpu jobs?

Cities with the most Software Engineer Gpu job openings:

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

The most popular types of Software Engineer Gpu jobs are:

What states have the most Software Engineer Gpu jobs?

States with the most job openings for Software Engineer Gpu jobs include:

Software Engineer Gpu jobs near you
Infographic showing various Software Engineer Gpu job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 87% Full Time, 8% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.

System Software Engineer - GPU & Accelerated Compute

Sunday Inc

Redwood City, CA • On-site

$211K - $251K/yr

Full-time

Re-posted 7 days ago

Job description

Join Us in Building the Future of Home Robotics
At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time.
We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we'd love to hear from you.
What to Expect
The ML & Robotics Infra team builds the foundational systems that every part of our robot perception, ML, controls and behavior runs on, and the developer infrastructure that lets us build, ship, and update that software quickly and safely on every robot in the fleet.
As a System Software Engineer on ML & Robotics Infra focused on GPU and accelerated compute, you'll own how every accelerated workload on the robot from model inference, SLAM/perception, and more gets data, gets scheduled and runs efficiently on shared compute. You'll work alongside teammates who own the runtime and our build and delivery infrastructure, and you'll partner cross-functionally with ML, SLAM/Perception, Controls and Hardware teams to ensure the GPU is a first-class, well-utilized resource that meets the latency and throughput requirements of a real-time robotic system operating in the home.
What You'll Do
You'll own and contribute to the accelerated compute layer of the ML & Robotics Infra, including:
  • Efficient model execution and switching: Reduce gpu kernel launch overheads and make swapping between models on the same device fast and predictable
  • GPU scheduling and time-slicing: Arbitrate GPU access across concurrent users (model inference, SLAM, and other robotics applications) with predictable latency
  • Camera pipeline: Drive low-latency transfer of camera frames into GPU memory, integrating with HW accelerate encode/decode (NVDEC/NVENC) where appropriate
  • CPU ↔ GPU data transfer: Build efficient, low-overhead data movement between host and device, including pinned memory, zero-copy paths, and asynchronous transfer patterns
  • CPU/GPU synchronization: Design synchronization primitives and patterns that minimize stalls and keep inference pipelines full

What You'll Bring
  • 2+ years of experience developing gpu systems software
  • Strong proficiency in CUDA and a systems language such as C++, C, or Rust
  • Solid understanding of GPU architecture, GPU workloads, and the tradeoffs involved in time-slicing and sharing the device across users
  • Hands-on experience with the CUDA ecosystem: CUDA runtime API, CUDA Graphs, and CUDA IPC
  • Familiarity with GPU sharing mechanisms such as MPS and MIG
  • Experience with GPU profiling tools such as Nsight Systems and Nsight Compute
  • Solid Linux fundamentals: scheduling, IPC, memory management, and performance tuning

Nice to Have
  • Contributions to CUDA libraries or other GPU programming libraries
  • Experience with camera pipeline integration and NVDEC/NVENC
  • Experience optimizing model inference on embedded GPU platforms (e.g., Jetson)
  • Experience with observability and tracing for GPU-accelerated workloads

At Sunday Robotics, we're building technology shaped by real people - curious, creative, and diverse. We're proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Even if you don't meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria - we don't want that to be the reason we miss out on great talent.

Apply