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Cuda Jobs in Arizona (NOW HIRING)

Prosum Inc.

Sr. 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 ...

Intel

AI Software Engineering Intern

Phoenix, AZ

  • Medical

  • Retirement

  • PTO

Graphics experience (GPU / CUDA) Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research. Internship ...

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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:

What are popular job titles related to Cuda jobs in Arizona?

For Cuda jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Cuda jobs in Arizona look for?

The top searched job categories for Cuda jobs in Arizona are:

Cuda jobs near you
Infographic showing various Cuda job openings in Arizona as of August 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Contract. Highlights an 78% Physical, 6% Hybrid, and 16% Remote job distribution.

Senior / Staff ML Training Optimization Engineer

3M HEALTHCARE

Phoenix, AZ • On-site

$140 - $210/hr

Other

Posted 13 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world‑class team, we’re unlocking the next era of autonomous transportation with technology that powers commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, we are growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

Responsibilities
  • Build standardized distributed training frameworks for research and production, drive our training towards new levels of stability and efficiency.
  • Comprehensively profile model runtime and memory to pinpoint performance bottlenecks.
  • Identify and evaluate emerging technologies that can be adopted into Waabi’s training and inference frameworks. Examples include designing new CUDA kernels, quantization‑aware training and inference, and compilation/deployment techniques.
  • Work with researchers and ML engineers on best‑practices for optimal resource usage.
  • Create and improve tooling and dashboards to ensure broad adoption of your work.
Qualifications
  • MS/PhD or Bachelors degree with a minimum of 4 years of industry experience in Computer Science, Robotics and/or similar technical field(s) of study.
  • Solid coding proficiency in a variety of coding languages including Python, C++ or Rust.
  • Experience in deep learning frameworks such as PyTorch or Jax.
  • Skilled in profiling CPU and GPU code using tools such as PyTorch Profiler and NVIDIA Nsight.
  • Open‑minded and collaborative team player with willingness to help others.
  • Passionate about self‑driving technologies, solving hard problems, and creating innovative solutions.
Bonus / Nice to have
  • Experience in identifying when custom CUDA kernels are needed, and implementing them.
  • Experience in Bazel in a monorepo environment, and integrating third‑party packages into dev environments.
  • Experience with Kubernetes‑based training platforms.
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