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Gpu Programmer Jobs in Arizona (NOW HIRING)

Accenture

AI & HPC Infrastructure Engineer

Scottsdale, AZ · On-site

$108K - $142K/yr

Deploy, configure, and manage XPU-based clusters (GPU, DPU, LPU, CPU) across bare-metal and containerized environments using workload schedulers (Slurm, Run:ai), Kubernetes orchestration, and ...

onsemi

Applications Engineer

Scottsdale, AZ · On-site

... GPU/AI compute platforms and largescale powerdelivery clusters. You will work closely with ... Engineering (focus on power electronics or related field) with 0 -2 years of relevant experience.

Rincon Research Corp

Sr. Software Engineer

Tucson, AZ · On-site

$229K - $280K/yr

What are the primary responsibilities in the Sr. Software Engineer position? * Responsible for ... Experience with developing GPU code using CUDA libraries * Familiarity with additional high-level ...

ON Semiconductor

Applications Engineer

Scottsdale, AZ · On-site

The Power Applications Engineer will drive the development, validation, and adoption of onsemi ... high-density GPU/AI compute platforms and large-scale power-delivery clusters. You will work ...

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Gpu Programmer information

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$11

$36

$64

How much do gpu programmer jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for gpu programmer in Arizona is $36.84, according to ZipRecruiter salary data. Most workers in this role earn between $23.99 and $47.93 per hour, depending on experience, location, and employer.

What does a GPU programmer do?

A GPU Programmer specializes in writing and optimizing code that runs on Graphics Processing Units (GPUs). They use parallel computing techniques and languages like CUDA or OpenCL to accelerate tasks such as graphics rendering, scientific simulations, and machine learning. Their work involves optimizing performance, managing memory efficiently, and ensuring compatibility across different hardware architectures.

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

To thrive as a GPU Programmer, you need a solid background in computer science, experience with parallel computing concepts, and proficiency in GPU programming languages like CUDA or OpenCL. Familiarity with development tools such as NVIDIA Nsight, profiling utilities, and version control systems is typically required, while relevant certifications in GPU computing can be beneficial. Strong problem-solving ability, collaboration skills, and attention to detail help differentiate top performers in this field. These skills are essential for optimizing code performance, successfully working in dynamic teams, and meeting the high computational demands of modern applications.

What are popular job titles related to Gpu Programmer jobs in Arizona?

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

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

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Gpu Programmer jobs near you
Infographic showing various Gpu Programmer job openings in Arizona as of August 2026, with employment types broken down into 84% Full Time, 6% Part Time, 2% Temporary, 7% Contract, and 1% Nights. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $76,633 per year, or $36.8 per hour.

Senior / Staff ML Training Optimization Engineer

3M HEALTHCARE

Phoenix, AZ • On-site

$140 - $210/hr

Other

Posted 15 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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