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Gpu Jobs (NOW HIRING)

Develop high-performance GPU primitives and abstractions to enable Waymo to scale its accelerator codebase across diverse GPU backends * Collaborate with Waymo's internal hardware team and external ...

GPU Kernel Engineer

San Francisco, CA · On-site

$190K - $250K/yr

About the role We are seeking a highly skilled GPU Kernel Engineer who is passionate about pushing the limits of performance on modern accelerators. In this role, you will design and optimize custom ...

Software Engineer, GPU

Mountain View, CA · On-site +1

$204K - $259K/yr

Develop high-performance GPU primitives and abstractions to enable Waymo to scale its accelerator codebase across diverse GPU backends * Collaborate with Waymo's internal hardware team and external ...

Software Engineer, GPU

Mountain View, CA · On-site

$204K - $259K/yr

Develop high-performance GPU primitives and abstractions to enable Waymo to scale its accelerator codebase across diverse GPU backends * Collaborate with Waymo's internal hardware team and external ...

Software Engineer, GPU

Manhattan, NY · On-site +1

$204K - $259K/yr

Develop high-performance GPU primitives and abstractions to enable Waymo to scale its accelerator codebase across diverse GPU backends * Collaborate with Waymo's internal hardware team and external ...

GPU Software Engineer

$138.20K - $185.30K/yr

GPU Software Engineer Location: USA(Remote) Role Summary We are seeking expert-level GPU Software Engineers to support a high-visibility platform initiative within the Maya program, focused on ...

Senior GPU Architect

Santa Clara, CA · On-site

$152.10K - $206.70K/yr

NVIDIA's GPU Architecture Group is looking for architects to contribute to the design of our proprietary profiler subsystem, the apparatus embedded in every GPU that enables our profiling and ...

We're seeking a GPU Performance Engineer to squeeze every last FLOP from our H100 infrastructure and optimize our model serving stack to its absolute limits. The Role You'll be our performance ...

Qualcomm's GPU Research Team is looking for talented GPU architects to help advance state-of-the-art 3D GPU capabilities in Ray Tracing, Neural Rendering, Geometry Processing, and Machine Learning.

Software Engineer - GPU Kernels

$143.30K/yr

This role focuses on designing high-performance GPU kernels and optimizing computation for machine learning operations, directly impacting production systems for millions of users. Responsibilities ...

We're seeking a GPU Performance Engineer to squeeze every last FLOP from our H100 infrastructure and optimize our model serving stack to its absolute limits. The Role You'll be our performance ...

Hudson River Trading (HRT) is looking for GPU Systems Engineers to help scale and evolve our exceptionally sophisticated HPC/AI research environment. Joining our Research and Development team, you ...

As a member of the Silicon Technologies GPU team, you will work across functions including Architecture, Power, Performance, Silicon Validation, Thermals and Technology. The job involves analyzing ...

As a GPU performance modeling engineer, you will be responsible for developing cycle-approximate perf C/C++ models in close collaboration with architects and designers. Additionally, you will analyze ...

Senior GPU Architect

Santa Clara, CA · On-site

$152.10K - $206.70K/yr

NVIDIA's GPU Architecture Group is looking for architects to contribute to the design of our proprietary profiler subsystem, the apparatus embedded in every GPU that enables our profiling and ...

GPU Software Engineer Location: Austin, TX Duration: Long Term Contract Roles and Responsibilities: * As a GPU Software Engineer, you will be equipped to develop GPU IP from the early Architectural ...

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Gpu information

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How much do gpu jobs pay per hour?

As of May 30, 2026, the average hourly pay for gpu in the United States is $54.94, according to ZipRecruiter salary data. Most workers in this role earn between $54.09 and $64.90 per hour, depending on experience, location, and employer.

What is a GPU job?

A GPU job refers to a computing task that utilizes a Graphics Processing Unit (GPU) for acceleration. GPUs are specialized processors designed for parallel processing, making them ideal for tasks like machine learning, scientific simulations, and rendering. Many software applications offload intensive computations to GPUs to improve performance and efficiency. Jobs related to GPUs can involve programming, optimization, and hardware configuration in fields like AI, gaming, and data analysis.

What are the key skills and qualifications needed to thrive as a GPU Engineer, and why are they important?

To thrive as a GPU Engineer, you need a solid background in computer engineering, mathematics, and programming languages such as C++ or CUDA, often supported by a relevant degree. Familiarity with GPU architectures, parallel computing frameworks, and tools like OpenCL or Vulkan is typically required. Analytical thinking, problem-solving, and teamwork are essential soft skills for innovating and debugging complex systems. These abilities are crucial for optimizing performance, ensuring compatibility, and driving advancements in graphics and computational workloads.

What are some common challenges faced by GPU engineers when optimizing performance for various applications?

GPU engineers often encounter challenges such as balancing high computational throughput with power efficiency, ensuring compatibility across different hardware architectures, and optimizing code for parallel processing. They must also troubleshoot bottlenecks in memory bandwidth and latency that can impact performance. Collaboration with software developers and hardware architects is crucial to identify and resolve these issues, and staying updated with the latest advances in GPU technologies is essential for continued success.

What is a GPU?

A GPU, or Graphics Processing Unit, is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images and graphics for display. While originally developed for rendering graphics in video games and visual applications, GPUs are now widely used for parallel processing tasks in areas such as artificial intelligence, data science, and scientific computing. Their architecture allows them to handle thousands of operations simultaneously, making them much faster than traditional CPUs for certain workloads.

What is the difference between Gpu vs Data Scientist?

AspectGpuData Scientist
Required CredentialsKnowledge of parallel computing, programming skills (CUDA, OpenCL)Degree in Computer Science, Statistics, or related fields; programming skills
Work EnvironmentHardware-focused, technical, often in R&D or engineering teamsData analysis, modeling, research in various industries
Industry UsageTech, gaming, AI, machine learningFinance, healthcare, tech, marketing

Gpu specialists focus on hardware and parallel processing for computing tasks, while data scientists analyze data to extract insights. Both roles require technical skills, but Gpu roles are more hardware-oriented, whereas data scientists focus on data analysis and modeling.

What cities are hiring for Gpu jobs? Cities with the most Gpu job openings:
What are the most commonly searched types of Gpu jobs? The most popular types of Gpu jobs are:
What states have the most Gpu jobs? States with the most job openings for Gpu jobs include:
What job categories do people searching Gpu jobs look for? The top searched job categories for Gpu jobs are:
Infographic showing various Gpu job openings in the United States as of May 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $114,281 per year, or $54.9 per hour.
GPU Software Engineer/GPU Architect

GPU Software Engineer/GPU Architect

Triune Infomatics Inc

San Jose, CA

$164.10K - $202.80K/yr

Other

Posted 5 days ago


Job description

Role: GPU Software Engineer/GPU Architect
Location: San Jose, CA
Duration: Long-term >> ongoing contract
 
Overview: We're looking for a strong GPU Software Engineer/GPU Architect to join a highimpact engineering team working on nextgeneration AI, GPU, and semiconductor technologies. This role focuses on GPU kernel development, memory architecture, and integration with modern inference systems such as vLLM and SGLang. You'll work onsite in San Jose, collaborating closely with a team of engineers building highperformance GPUaccelerated systems.
  • Develop and optimize CUDA/ROCm kernels for AI workloads
  • Work with HBM, memory hierarchy, thread scheduling, and P2P communication
  • Integrate GPU kernels with vLLM, SGLang, and other inference servers
  • Build highperformance components in C++ and Python
  • Support AI frameworks such as PyTorch and TensorFlow
  • Optimize multiGPU scaling, KVcache, and attention kernels
  • Profile and debug GPU workloads using Nsight, rocprof, etc.
  • Collaborate with crossfunctional GPU, AI, and semiconductor teams
Required Skills:
  • Strong experience with CUDA, ROCm/HIP, OpenCL, or MPI
  • Deep understanding of GPU architecture, HBM, memory models, and thread hierarchies
  • Handson experience with AMD/NVIDIA GPU software stacks
  • Expertlevel C++ and Python
  • Experience with PyTorch or TensorFlow
  • Experience with vLLM, SGLang, or similar inference systems
Preferred Skills:
  • RDMA, RoCE, InfiniBand, or Infinity Fabric
  • Distributed inference/training or HPC experience
  • Semiconductor or hardwareadjacent experience