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Cuda Jobs (NOW HIRING)

CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA ( You will design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the ...

Senior DL Compiler Engineer -CUDA Tile

Santa Clara, CA ยท On-site

$143K - $189K/yr

CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA ( You will design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the ...

Senior DL Compiler Engineer -CUDA Tile

OR ยท On-site +1

$122K - $161K/yr

CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA ( You will design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the ...

Senior DL Compiler Engineer -CUDA Tile

Redmond, WA ยท On-site

$137K - $180K/yr

CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA ( You will design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the ...

C++/CUDA Signal Processing Engineer Company: Dalcom Engineering Location: Aberdeen Proving Ground, MD Salary: $140,000-$176,000 Position Overview: Dalcom Engineering is currently seeking a software ...

At the center of this platform are CUDA Core Libraries that enable developers to build fast, reliable, and scalable GPU-accelerated software. We are hiring a Senior Software Engineer to develop the ...

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CUDA information

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$111.5K

$206K

How much do cuda jobs pay per year?

As of Aug 16, 2026, the average yearly pay for cuda in the United States is $200,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $205,000.00 and $205,000.00 per year, depending on experience, location, and employer.

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 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.

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Infographic showing various Cuda job openings in the United States as of August 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 82% Physical, 6% Hybrid, and 12% Remote job distribution, with an average salary of $200,510 per year, or $96.4 per hour.

Software Engineer - Software Engineer - GPU, C++, OpenCL, CUDA

Hudson IT

Waukesha, WI โ€ข On-site

Other

Posted 2 days ago

New


Job description

Position: Software Engineer - GPU, C++, OpenCL, CUDA
Location: Waukesha, WI (Onsite)
Exp: 5 - 9 yrs
Key Skills: GPU, C++, OpenCL, CUDA, OneAPI, Matlab
Job Requirements
The CT Program is working on upgrading CT scanners used worldwide. The center is currently concentrating on the ongoing enhancement of the next generation of CT machines, including their essential workflows and applications. For that purpose, proficient and experienced resources are required.
Primary Objective:
  1. Leverage proprietary software platform to implement image processing algorithms on GPUs. (C++/OpenCL/CUDA/OneAPI)
  2. Improve image chain performance using heterogeneous high-performance computing (HPC) to meet customer expectations
  3. Ensure quality and compliance of productized code per regulatory expectations

Detailed Requirements:
  1. Productized CT image processing algorithms on GPU, including ported algorithms from Matlab to GPU, or OpenCL to CUDA
  2. Improved image chain & algorithm performance compared to initial benchmarks
  3. Perform GPU profiling, identify algorithm bottlenecks, troubleshoot and resolve performance issues
  4. Improve GPU utilization leveraging heterogenous HPC knowledge.
  5. Perform testing, reliability analysis, performance benchmarks and document results
  6. Execute test procedures with high quality and rigor, following Good Documentation Practices

Work Experience
Skills:
  1. Programming Languages: C++, OpenCL, CUDA, OneAPI
  2. Image Processing Algorithms: Implementation and optimization on GPUs
  3. High-Performance Computing (HPC): Knowledge of heterogeneous HPC
  4. Profiling and Performance Analysis: GPU profiling, identifying bottlenecks, troubleshooting, and resolving performance issues
  5. Testing and Documentation: Performing testing, reliability analysis, performance benchmarks, and documenting results following Good Documentation Practices

Additional Experience:
Productizing Algorithms: Experience in productizing CT image processing algorithms on GPU
Porting Algorithms: Experience in porting algorithms from Matlab to GPU or OpenCL to CUDA
Improving Performance: Proven track record of improving image chain and algorithm performance compared to initial benchmarks
Quality and Compliance: Ensuring quality and compliance of productized code per regulatory expectations
Best regards,
Prasad Kalsekar | Hudson Manpower
Email: