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ConfigUSA

CUDA Programmer

Waukesha, WI · On-site

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 ...

Dalcom LLC

C++/CUDA-Signal Processing Engineer

Aberdeen, MD · On-site

$140K - $176K/yr

C++/CUDA Signal Processing Engineer Company: Dalcom Engineering Location: Aberdeen Proving Ground, MD Salary: $140,000-$176,000 Position Overview: Dalcom Engineering is currently seeking a software ...

Parsons

C++ / CUDA Signal Processing Engineer

Aberdeen, MD · On-site

$100K - $176K/yr

Parsons welcomes an exceptional Signal Processing Engineer skilled in C++ and CUDA programming to join our on-going Science and Technology (S&T) efforts at one of the Army's premier R&D Centers at ...

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How much do cuda programmer jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for cuda programmer in the United States is $39.54, according to ZipRecruiter salary data. Most workers in this role earn between $25.72 and $51.44 per hour, depending on experience, location, and employer.

What are the most common challenges faced by Cuda Programmers in their daily work?

Cuda Programmers often encounter challenges related to optimizing code performance and efficiently managing memory on GPU architectures. Debugging and profiling can be complex, as issues may arise from both the code and hardware-specific elements, requiring close attention to parallelization and bottlenecks. Collaboration is key, as you’ll typically work closely with software engineers, data scientists, or researchers to integrate and optimize code for specialized workflows. Successfully navigating these challenges helps drive significant performance improvements and innovation in high-performance computing applications.

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

To thrive as a Cuda Programmer, you need strong programming skills in C/C++ and parallel computing, with a solid understanding of GPU architectures and CUDA development. Familiarity with CUDA libraries, performance profiling tools, and platforms like NVIDIA Nsight or Visual Studio is often required, while certifications from NVIDIA can be advantageous. Problem-solving abilities, attention to detail, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can optimize complex algorithms, work efficiently on high-performance computing projects, and collaborate smoothly with multidisciplinary teams.

What is a CUDA Programmer job?

A CUDA Programmer develops high-performance parallel computing applications using NVIDIA's CUDA (Compute Unified Device Architecture) framework. They optimize algorithms to run efficiently on GPUs, accelerating tasks such as machine learning, scientific simulations, and real-time data processing. This role requires proficiency in C/C++, an understanding of GPU architectures, and experience with parallel computing concepts to maximize performance.

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Cuda Programmer jobs near you
Infographic showing various Cuda Programmer job openings in the United States as of June 2026, with employment types broken down into 91% Full Time, 6% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 87% Physical, 6% Hybrid, and 7% Remote job distribution, with an average salary of $82,234 per year, or $39.5 per hour.

CUDA Programmer

ConfigUSA

Waukesha, WI • On-site

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Posted 22 days ago

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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.