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Gpu Programmer Jobs in Wisconsin (NOW HIRING)

ConfigUSA

CUDA Programmer

Waukesha, WI · On-site

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 ...

Gehc

Senior Software Engineer

Waukesha, WI · On-site

$122K - $161K/yr

Summary As a Senior Software Engineer, you will own the design, development, and delivery of ... Experience with GPU, Drivers, BIOS, Networking, GPU technologies. * Demonstrated expertise in Linux ...

GE HealthCare

Senior Software Engineer

Waukesha, WI · On-site

$122K - $161K/yr

Summary As a Senior Software Engineer, you will own the design, development, and delivery of next ... Experience with GPU, Drivers, BIOS, Networking, GPU technologies. * Demonstrated expertise in Linux ...

Serve Robotics

$225K - $260K/yr

This includes ensuring data is efficiently loaded, distributed, and processed across large GPU ... Work closely with ML scientists and other engineers to integrate new models, experiments, and ...

GE HealthCare

Senior Software Engineer

Waukesha, WI · On-site

$122K - $161K/yr

As a Senior Software Engineer, you will own the design, development, and delivery of next ... GPU technologies. • Automated testing experience test case development, maintenance, and ...

LRS

Software Engineer, Intern

Waukesha, WI · On-site

$23.50/hr

You'll contribute to algorithm development and highperformance computing (GPU/CPU) on Linux, with a ... Familiarity with objectoriented programming and common design patterns. Analytical and ...

GE HealthCare

Senior Software Engineer

Waukesha, WI · On-site

$122K - $161K/yr

Summary As a Senior Software Engineer, you will own the design, development, and delivery of next ... Experience with Virtualization, Device Drivers, BIOS, Networking, and GPU technologies. * Automated ...

Gehc

Senior Software Engineer

Waukesha, WI

$122K - $161K/yr

Summary As a Senior Software Engineer, you will own the design, development, and delivery of ... Experience with Virtualization, Device Drivers, BIOS, Networking, and GPU technologies. * Automated ...

Gehc

Senior Manager - Software Engineering

Waukesha, WI · On-site

Summary The Senior Engineering Manager for Compute, Cybersecurity & Serviceability is a critical ... Deep expertise in Linux systems and distributed compute architectures, including CPU- and GPU-based ...

Gehc

Director of Engineering, Architecture

Waukesha, WI · On-site

$164K - $246K/yr

Knowledge of GPU computing (CUDA or equivalent), parallel processing, and high-performance ... You'll work alongside world-class engineers, architects, and product leaders to build scalable ...

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Gpu Programmer information

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$12

$39

$69

How much do gpu programmer jobs pay per hour?

As of Jul 26, 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 develops software that leverages graphics processing units to perform parallel computations, often for rendering graphics, scientific simulations, or machine learning tasks. They typically use programming languages like CUDA or OpenCL and have knowledge of graphics APIs and hardware architecture.

Which IT job is the highest paid?

In the IT industry, roles such as Chief Technology Officer (CTO), Solutions Architect, and Cloud Engineering Manager tend to be among the highest paid, often earning six-figure salaries or more. Specialized skills in areas like cybersecurity, AI, and cloud computing, along with extensive experience and certifications, can significantly increase earning potential.

What engineer makes $500,000 a year?

Highly experienced GPU programmers or senior graphics engineers in top tech companies can earn salaries approaching or exceeding $500,000 annually, especially with bonuses and stock options. Such roles typically require advanced skills in graphics programming, CUDA, or shader development, along with extensive industry experience and often a master's or Ph.D. degree.

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 the typical daily responsibilities of a GPU Programmer?

As a GPU Programmer, your daily tasks often involve designing, developing, and optimizing algorithms that leverage GPU architectures for increased performance in applications such as graphics rendering, scientific computing, or machine learning. You will routinely write and debug parallel code, profile workloads to find bottlenecks, and collaborate with software engineers, data scientists, and hardware specialists to integrate GPU-accelerated solutions. Documentation and code reviews are also important parts of your routine to ensure maintainability and knowledge sharing within the team. This role typically combines independent project work with regular cross-disciplinary collaboration, making adaptability and teamwork key to success.

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.

How much do GPU engineers make?

GPU engineers typically earn a median salary ranging from $90,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in graphics programming, parallel computing, or CUDA may command higher salaries. Compensation can also include bonuses and stock options in larger tech firms.
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:
Gpu Programmer jobs near you
Infographic showing various Gpu Programmer job openings in Wisconsin as of July 2026, with employment types broken down into 90% Full Time, 5% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 87% Physical, 5% Hybrid, and 8% 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

Posted 12 hours 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.