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Gpu Programmer Jobs in Wisconsin (NOW HIRING)

Profile and tune GPU applications for performance, memory efficiency, and scalability. * Work with CPU-GPU parallel programming models and optimize data transfer. * Leverage NVIDIA libraries (CUDA ...

WI · On-site

$150 - $200/hr

GPU Bare MetalRequired Skills * Proven ability to orchestrate bare metal linux systems at scale ... Network engineering experience with VyOS platforms. What You'll Be Working On: * Provisioning and ...

Familiarity with GPU technologies; CUDA or OpenCL Desired Characteristics We are seeking engineers ... who demonstrate exceptional potential through curiosity, ownership, learning agility, and technical ...

Familiarity with GPU technologies; CUDA or OpenCL Desired Characteristics We are seeking engineers ... who demonstrate exceptional potential through curiosity, ownership, learning agility, and technical ...

WI · On-site

$150 - $200/hr

More recently, GPU deep learning ignited modern AI -- the next era of computing -- with the GPU ... We are looking for a Verification Engineer, Compute Performance to join our Compiler Verification ...

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WI · On-site

$250/hr

Own the physical layer of the AI compute environment - GPU compute, storage, network fabric ... Empower the Security SRE Lead to maintain a world‑class security posture across the ...

WI · On-site

$150 - $200/hr

We specialize in dedicated GPU cloud solutions tailored to the unique needs of startups, research ... Position Summary We are seeking a Cloud Engineer with deep expertise in GCP Landing Zones to join ...

WI · On-site

$200 - $250/hr

Experience with GPU programming, CUDA, OpenCL, parallel computing, or hardware-accelerated software optimization. * Knowledge of networking protocols, distributed systems, edge computing, embedded ...

WI · On-site

$150 - $200/hr

Be a technical specialist on GPU and networking products, partnering with account, program, architecture, and engineering teams to support design‑in, integration readiness, issue resolution, and ...

WI · On-site

$150 - $200/hr

Its engineers build critical infrastructure to eliminate friction in scientific research ... Design, configure, and manage a high‑performance compute fleet comprising large‑scale GPU ...

HPC Performance Engineer

Oregon, WI · On-site

$150 - $200/hr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... Our performance engineers analyze High Performance Computing (HPC) applications with the intent of ...

WI · On-site

$150 - $200/hr

We specialize in dedicated GPU cloud solutions tailored to the unique needs of startups, research ... Position Summary We are seeking a Sr. Network Engineer to join our Engineering team. This ...

WI · On-site

$150 - $200/hr

Build datacenter GPU dockers and containers for customer testing and deployment. * Qualify and ... ACADEMIC CREDENTIALS: * Bachelor's or Master's degree in computer engineering, Electrical ...

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Gpu Programmer information

See Wisconsin salary details

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How much do gpu programmer jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for gpu programmer in Wisconsin is $39.91, according to ZipRecruiter salary data. Most workers in this role earn between $25.96 and $51.92 per hour, depending on experience, location, and employer.

What does a GPU programmer do?

A GPU Programmer specializes in writing and optimizing code that runs on Graphics Processing Units (GPUs). They use parallel computing techniques and languages like CUDA or OpenCL to accelerate tasks such as graphics rendering, scientific simulations, and machine learning. Their work involves optimizing performance, managing memory efficiently, and ensuring compatibility across different hardware architectures.

What are the key skills and qualifications needed to thrive in the GPU programmer position, and why are they important?

To thrive as a GPU Programmer, you need a solid background in computer science, experience with parallel computing concepts, and proficiency in GPU programming languages like CUDA or OpenCL. Familiarity with development tools such as NVIDIA Nsight, profiling utilities, and version control systems is typically required, while relevant certifications in GPU computing can be beneficial. Strong problem-solving ability, collaboration skills, and attention to detail help differentiate top performers in this field. These skills are essential for optimizing code performance, successfully working in dynamic teams, and meeting the high computational demands of modern applications.

What are popular job titles related to Gpu Programmer jobs in Wisconsin?

For Gpu Programmer jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Gpu Programmer jobs in Wisconsin look for?

The top searched job categories for Gpu Programmer jobs in Wisconsin are:

Infographic showing various Gpu Programmer job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 92% Full Time, 5% Part Time, and 2% Contract. Highlights an 76% Physical, 7% Hybrid, and 17% Remote job distribution, with an average salary of $83,004 per year, or $39.9 per hour.

CUDA Programmer

ConfigUSA

Waukesha, WI • On-site

Contractor

Re-posted 13 days ago


Job description

CUDA Programmer
Location: Waukesha, WI

We are seeking a skilled CUDA Programmer to design, develop, and optimize high-performance applications on NVIDIA GPUs. The role focuses on accelerating compute-intensive workloads, optimizing memory usage, and collaborating with system and application teams to maximize GPU performance.

Key Responsibilities

  • Profile and tune GPU applications for performance, memory efficiency, and scalability.
  • Work with CPU–GPU parallel programming models and optimize data transfer.
  • Leverage NVIDIA libraries (CUDA, cuBLAS, cuDNN, NCCL as applicable).
  • Collaborate with system, compute, or AI/ML teams to integrate GPU-accelerated components.
  • Debug GPU kernels and address performance bottlenecks using NVIDIA profiling tools.
  • Ensure portability and performance across different NVIDIA GPU architectures.

Required Skills

  • Strong experience in CUDA programming and parallel computing concepts.
  • In-depth understanding of NVIDIA GPU architecture (threads, warps, SMs, memory hierarchy).
  • Proficiency in C/C++ for high-performance computing.
  • Experience with CUDA profiling and debugging tools (Nsight, nvprof).
  • Solid understanding of multi-threading, memory optimization, and performance tuning.

Preferred Skills

  • Experience with AI/ML, HPC, or graphics workloads on GPUs.
  • Familiarity with multi-GPU programming and communication frameworks (NCCL, MPI).
  • Exposure to Python bindings (CUDA Python, PyTorch extensions).
  • Experience with Linux-based development environments.