1

Cuda Programming Jobs in Wisconsin (NOW HIRING)

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 ...

Software Engineer Role Our Healthcare client is looking to bring aboard two to three Software ... Transition algorithms from platforms such as MATLAB or OpenCL to CUDA. * Analyze and enhance image ...

Software Engineer role 12-month contract Location: Hybrid onsite in Waukesha, WI Our Healthcare ... Transition algorithms from platforms such as MATLAB or OpenCL to CUDA. * Analyze and enhance image ...

... programming technologies such as CUDA and/or OpenCL Familiarity with scripting languages such as Bash or Python Strong foundation in mathematics The pay for this internship position is $23.50 per ...

SysOps Administrator, DevOps Engineer, Solutions Architect) • 1+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack • Experience in a client facing role Company

New

Senior Software Engineer - Imaging (C++)

Waukesha, WI · On-site

$122K - $161K/yr

Summary As a Senior Software Engineer, you will act as a technical lead, driving the design and development of clinical applications and features using C++, CUDA, and HLSL, with a special emphasis on ...

Cuda Programming information

See Wisconsin salary details

$28

$54

$82

How much do cuda programming jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for cuda programming in Wisconsin is $54.86, according to ZipRecruiter salary data. Most workers in this role earn between $44.42 and $64.04 per hour, depending on experience, location, and employer.

What is the difference between Cuda Programming vs GPU Developer?

AspectCuda ProgrammingGPU Developer
Required CredentialsKnowledge of CUDA, C/C++, parallel computingKnowledge of GPU architecture, CUDA, OpenCL, C/C++
Work EnvironmentHigh-performance computing, scientific research, AIGraphics, gaming, scientific visualization, AI
Industry UsageTech companies, research labs, AI firmsGaming, entertainment, tech, research

While Cuda Programming focuses specifically on writing code using NVIDIA's CUDA platform for parallel processing, GPU Developers have a broader role that includes designing, optimizing, and implementing GPU-based solutions across various platforms and technologies. Both roles require knowledge of GPU architecture and programming languages like C/C++, but GPU Developers often work on a wider range of applications beyond CUDA-specific projects.

What are popular job titles related to Cuda Programming jobs in Wisconsin? For Cuda Programming jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Cuda Programming jobs in Wisconsin look for? The top searched job categories for Cuda Programming jobs in Wisconsin are:
Infographic showing various Cuda Programming job openings in Wisconsin as of June 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $114,118 per year, or $54.9 per hour.

CUDA Programmer

ConfigUSA

Waukesha, WI • On-site

Contractor

Posted 23 days ago

Be an early applicant


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.