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Entry Level Cuda Developer Jobs (NOW HIRING)

iSoftStone

Associate AI Developer

White Plains, NY · On-site

$20/hr

This training-based, early-career role is ideal for entry level candidates eager to grow into hands ... AWS (Bedrock, SageMaker), Azure (AI Foundry/AI Studio, Azure OpenAI), NVIDIA (CUDA, NIM, Triton ...

Cgg

Research Geophysicist

Houston, TX · Hybrid

Excellent coding skills with one or more programming languages, such as C/C++, CUDA, FORTRAN ... Performance based monthly bonus averaging at 10-15% at entry level ( contingent on financial ...

Viridien

Research Geophysicist

Houston, TX · Hybrid

Excellent coding skills with one or more programming languages, such as C/C++, CUDA, FORTRAN ... Performance based monthly bonus averaging at 10-15% at entry level ( contingent on financial ...

Viridien

Research Geophysicist

Houston, TX · Hybrid

Excellent coding skills with one or more programming languages, such as C/C++, CUDA, FORTRAN ... Performance based monthly bonus averaging at 10-15% at entry level ( contingent on financial ...

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Entry Level Cuda Developer information

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$29.5K

$100.3K

$241.5K

How much do entry level cuda developer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for entry level cuda developer in the United States is $100,265.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,500.00 and $106,000.00 per year, depending on experience, location, and employer.

What does an entry level CUDA developer do?

An Entry Level CUDA Developer is responsible for writing and optimizing software that uses NVIDIA's CUDA platform to accelerate computations on GPUs. Their tasks often include converting existing code to utilize parallel processing, debugging GPU-related issues, and collaborating with senior developers to improve application performance. These developers typically work with C or C++ and need a strong understanding of parallel programming concepts. Entry-level roles focus on learning best practices, gaining experience with CUDA tools, and contributing to larger software projects.

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

To thrive as an Entry Level CUDA Developer, you need a solid understanding of C/C++ programming, parallel computing concepts, and a relevant degree in computer science or engineering. Familiarity with NVIDIA CUDA Toolkit, GPU architectures, and version control systems like Git is typically required. Problem-solving abilities, attention to detail, and effective teamwork are essential soft skills in this role. These skills and qualities are crucial for efficiently developing high-performance GPU applications and collaborating on complex technical projects.

What are some common challenges faced by entry level CUDA developers, and how can they overcome them?

Entry level CUDA developers often encounter challenges related to understanding parallel programming concepts and optimizing code for GPU architectures. Debugging and profiling CUDA applications can also be complex due to the asynchronous nature of GPU operations. To overcome these hurdles, new developers are encouraged to leverage available profiling tools, engage in code reviews with more experienced colleagues, and build a solid foundation in GPU memory management. Collaborating closely with team members and seeking mentorship can accelerate learning and help resolve technical roadblocks more efficiently.

What is the difference between Entry Level Cuda Developer vs Entry Level GPU Programmer?

AspectEntry Level Cuda DeveloperEntry Level GPU Programmer
Required CredentialsKnowledge of CUDA, C/C++, basic understanding of GPU architectureFamiliarity with GPU programming, CUDA or OpenCL, programming skills in C/C++
Work EnvironmentSoftware development teams, research labs, tech companiesGraphics and compute-focused teams, gaming, scientific computing
Industry UsageHigh-performance computing, AI, scientific simulationsGraphics rendering, gaming, visualization

Entry Level Cuda Developers and Entry Level GPU Programmers share foundational knowledge of GPU programming and often work in similar environments. However, CUDA Developers focus specifically on NVIDIA's CUDA platform for compute tasks, while GPU Programmers may work with multiple APIs like OpenCL or Vulkan for graphics and compute. Both roles are essential in tech industries leveraging GPU acceleration, but CUDA Developers typically require deeper expertise in CUDA-specific tools and workflows.

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Entry Level Cuda Developer jobs near you
Infographic showing various Entry Level Cuda Developer job openings in the United States as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $100,265 per year, or $48.2 per hour.

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

Hudson IT

Waukesha, WI • On-site

Other

Posted 5 days ago

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:

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