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$28

$56

$84

How much do cuda programming jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for cuda programming in Chicago, IL is $56.04, according to ZipRecruiter salary data. Most workers in this role earn between $45.34 and $65.43 per hour, depending on experience, location, and employer.

What is the difference between Cuda Programming vs GPU Developer?

AspectCuda ProgrammingGPU Developer
Required CredentialsKnowledge of CUDA, C/C++, parallel computingKnowledge of GPU architecture, CUDA, OpenCL, C/C++
Work EnvironmentHigh-performance computing, scientific research, AIGraphics, gaming, scientific visualization, AI
Industry UsageTech companies, research labs, AI firmsGaming, entertainment, tech, research

While Cuda Programming focuses specifically on writing code using NVIDIA's CUDA platform for parallel processing, GPU Developers have a broader role that includes designing, optimizing, and implementing GPU-based solutions across various platforms and technologies. Both roles require knowledge of GPU architecture and programming languages like C/C++, but GPU Developers often work on a wider range of applications beyond CUDA-specific projects.

Are CUDA programmers in demand?

CUDA programmers are in high demand due to the growing need for high-performance computing in fields like artificial intelligence, scientific research, and data processing. Skills in parallel programming, GPU architecture, and CUDA toolkit are highly valued, and job opportunities are expected to grow as industries adopt GPU acceleration for complex tasks.

What does a CUDA programming developer do?

A CUDA programming developer writes software that leverages NVIDIA's CUDA platform to perform parallel processing on GPUs, optimizing computational tasks such as scientific simulations, machine learning, and image processing. They typically work with C++ and CUDA-specific libraries, debugging and optimizing code for high performance in environments that require intensive data processing.

What are popular job titles related to Cuda Programming jobs in Chicago, IL?

For Cuda Programming jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Cuda Programming jobs in Chicago, IL look for?

The top searched job categories for Cuda Programming jobs in Chicago, IL are:

Cuda Programming jobs near you
Infographic showing various Cuda Programming job openings in Chicago, IL as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 69% In-person, and 31% Remote job distribution, with an average salary of $116,561 per year, or $56 per hour.

CUDA Engineer - Kernel Optimization - AI Trainer

Mercor

Chicago, IL • On-site, Remote

$144K/yr

Full-time

Posted yesterday

New

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: CUDA Engineering Expert
Type: Contract
Compensation: $500/hour
Location: Remote

Role Responsibilities

  • Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization.
  • Use profiler metrics like L2 cache hit rate and occupancy to guide kernel improvements.
  • Review GPU kernel implementations and identify bottlenecks without deep algorithmic background.
  • Write and modify C++17, Python, and GPU programming code.
  • Apply expertise in CUDA, HIP, and shader programming to improve performance.
  • Document optimization decisions clearly, focusing on profiler metrics' utility.

Qualifications

Must-Have

  • Available to work at least 20 hrs/wk.
  • Fluent in core C++ features through C++17.
  • Working knowledge of Python and Git.
  • Fluent in one GPU programming model like CUDA or HIP.
  • 1+ year of professional or research experience with GPUs.
  • Strong understanding of GPU profiler performance metrics.

Preferred

  • Experience with CUDA, HIP, and CUDA C++ Core Libraries.
  • Experience optimizing kernels for NVIDIA Blackwell hardware.
  • Familiarity with NSight Compute.
  • Prior experience with NVIDIA, AMD, or Qualcomm.
  • Open-source contributions related to GPU kernel optimization.

Application Process (Takes 20–30 mins to complete)

  • Submit your resume or relevant technical background.
  • Qualified applicants may complete a brief technical assessment or submit additional information.

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.


#hiringmercor