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Cuda Jobs in Arizona (NOW HIRING)

CUDA Developer - Remote

Phoenix, AZ · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your ...

Design, implement, and optimize GPU software using CUDA, WebGPU, or GLSL . * Profile and optimize GPU kernels and shaders for performance and efficiency. * Develop host-side logic and GPU ...

Design, implement, and optimize GPU software using CUDA, WebGPU, or GLSL . * Profile and optimize GPU kernels and shaders for performance and efficiency. * Develop host-side logic and GPU ...

Machine Learning Engineer

Phoenix, AZ · On-site

$130K - $150K/yr

Responsibilities include eliminating hardware bottlenecks through CUDA kernel tuning and GPU parallel computing, ensuring deep learning models and CV algorithms seamlessly processing massive, high ...

Performance Engineer

Phoenix, AZ · On-site

$55 - $60/hr

... CUDA, Triton, ROCm/HIP) and low-level libraries (cuBLAS, cuDNN, CUTLASS) Inference runtimes/serving engines: TensorRT(-LLM), ONNX Runtime, vLLM, SGLang, Triton Inference Server LLM inference ...

Senior Software Engineer

Phoenix, AZ · On-site

$121K - $160K/yr

Knowledge of C/C++ low-level optimization, CUDA, or parallel compute systems. This role offers competitve pay, hybrid work options, and comprehensive health benefits. Apply now If you're ready to ...

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Cuda information

What is a CUDA developer?

A CUDA job typically involves developing, optimizing, and implementing parallel computing applications using NVIDIA's CUDA platform. CUDA (Compute Unified Device Architecture) enables developers to leverage the power of GPUs for high-performance computing tasks such as deep learning, simulations, and scientific computing. Professionals in this role often work with C, C++, or Python, using CUDA libraries and frameworks to accelerate processing. Strong knowledge of parallel programming, memory management, and GPU architecture is essential for success in this field.

What are some common challenges faced when working as a CUDA developer, and how can they be addressed?

CUDA Developers often encounter challenges such as debugging complex parallel code, optimizing memory usage, and ensuring compatibility across different GPU architectures. To address these, it's important to leverage profiling tools like NVIDIA Nsight to identify bottlenecks and inefficiencies. Collaborating closely with team members, such as data scientists and software engineers, can also help in resolving integration issues and achieving better performance. Staying updated with the latest CUDA Toolkit releases and best practices is key to overcoming these challenges and delivering robust GPU-accelerated applications.

What are the key skills and qualifications needed to thrive as a CUDA developer, and why are they important?

To thrive as a CUDA Developer, you need strong programming skills in C/C++, a solid understanding of parallel computing concepts, and experience with GPU architectures. Familiarity with the CUDA toolkit, NVIDIA GPUs, and related profiling/debugging tools is typically required, and certifications in GPU programming can be advantageous. Analytical thinking, problem-solving, and effective communication are essential soft skills for optimizing code and collaborating with cross-functional teams. These skills are crucial for developing high-performance applications that leverage GPU acceleration, ensuring efficiency and innovation in compute-intensive fields.

What is the difference between Cuda vs GPU Developer?

AspectCudaGPU Developer
Required CredentialsKnowledge of CUDA programming, often with a background in computer science or engineeringExperience with GPU programming, CUDA, OpenCL, or similar; often requires a degree in computer science or related fields
Work EnvironmentPrimarily focused on developing and optimizing CUDA-based applications for NVIDIA GPUsDesigning, developing, and maintaining GPU-accelerated applications across various platforms and hardware
Industry UsageUsed mainly in high-performance computing, AI, and scientific research involving NVIDIA GPUsApplied across gaming, scientific computing, AI, and multimedia industries

In summary, CUDA is a specialized skill set focused on programming NVIDIA GPUs using CUDA, while a GPU Developer has a broader role that may include using various GPU programming tools and working across multiple platforms. CUDA is a subset of the skills a GPU Developer might possess, making them closely related but distinct roles.

What are the most commonly searched types of Cuda jobs in Arizona?

The most popular types of Cuda jobs in Arizona are:

Infographic showing various Cuda job openings in Arizona as of August 2026, with employment types broken down into 96% Full Time, 3% Part Time, and 1% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

CUDA Developer - Remote

Phoenix, AZ • Remote

$60 - $100/hr

Full-time

Posted 19 days ago


Job description

CUDA Engineering Expert

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your expertise in CUDA, C++, and GPU programming to analyze, optimize, and improve high-performance GPU kernels.

No prior AI experience is required.

Key Responsibilities
  • Analyze, profile, and optimize GPU kernels using CUDA and profiling tools.

  • Identify performance bottlenecks and develop targeted optimization strategies.

  • Refactor C++ and CUDA code for efficiency and maintainability.

  • Develop shader logic using GLSL and WebGPU.

  • Document optimization processes, findings, and performance improvements.

  • Contribute to GPU architecture and performance discussions.

  • Collaborate with remote, cross-functional teams.

Required Qualifications
  • Strong expertise in CUDA programming and GPU kernel optimization.

  • Advanced C++ development skills.

  • Hands-on experience with GLSL and WebGPU.

  • Experience using GPU profiling tools such as NVIDIA Nsight or similar.

  • Strong understanding of GPU performance and architecture.

  • Excellent analytical, problem-solving, and technical communication skills.

  • Ability to work effectively in a remote environment.

Preferred Qualifications
  • Experience with high-performance computing or GPU-accelerated applications.

  • Experience optimizing workloads across different GPU architectures.

  • Background in graphics, compute shaders, or AI/ML acceleration.