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Cuda Developer Jobs (NOW HIRING)

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

... developer skilled in C++ and CUDA programming, to support Science and Technology (S&T) efforts for radar and signal systems at Aberdeen Proving Ground. About Us: Founded in 1998, Dalcom Engineering ...

Nvidia

OR

$122K - $161K/yr

Improve developer experience across the stack: CI, tests, benchmarks, packaging, examples, and docs. * Collaborate with senior CUDA engineers in design reviews, code reviews, and open-source-style ...

Nvidia

OR

$122K - $161K/yr

... other developer tools teams. * Apply your own knowledge and skills to build tools that are ... Expertise in CUDA kernel programming and profiling. * Outstanding interpersonal skills and the ...

Nvidia

OR

$122K - $161K/yr

Familiarity with deep learning accelerator architectures such as the GPU and hands-on experience with CUDA programming and kernel optimization. * A strong analytical approach with experience using ...

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How much do cuda developer jobs pay per year?

As of Jun 6, 2026, the average yearly pay for cuda developer in the United States is $111,845.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $130,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Cuda Developers in their daily work?

Cuda Developers often encounter challenges related to optimizing code for maximum performance while managing the unique memory hierarchies and parallel processing features of GPU architectures. Debugging and profiling GPU code can be more complex than standard CPU programming, requiring specialized tools and a strong understanding of concurrency. Collaboration with data scientists, machine learning engineers, and software architects is common, as Cuda Developers often integrate their code into larger, multi-disciplinary projects. These challenges make the role both stimulating and rewarding for those who enjoy solving intricate computational problems.

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

To thrive as a Cuda Developer, you need strong proficiency in C/C++ programming, parallel computing concepts, and hands-on experience with NVIDIA CUDA architecture. Familiarity with GPU development tools such as NVIDIA Nsight, CUDA Toolkit, and relevant certifications can further validate your expertise. Problem-solving skills, attention to detail, and effective collaboration are valuable soft skills in this position. These capabilities are crucial for efficiently developing, debugging, and optimizing high-performance GPU-accelerated applications in demanding computational environments.

What is a Cuda Developer job?

A CUDA Developer is a software engineer who specializes in programming using NVIDIA's CUDA (Compute Unified Device Architecture) platform. They leverage parallel computing to optimize and accelerate applications, mainly in fields like AI, scientific computing, and high-performance computing. Their responsibilities often include writing GPU-accelerated code, optimizing performance, and working with frameworks like TensorFlow or PyTorch.

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Cuda Developer jobs near you

CUDA Programmer

ConfigUSA

Waukesha, WI • On-site

Contractor

Posted 10 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.