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Gpu Entry Level Jobs (NOW HIRING)

Muon Space

Software Engineer, Entry-Level

San Jose, CA

$142K - $169K/yr

... Entry-level software engineers are expected to bring significant skills and training, and then to ... GPU programming or other relevant disciplines * Experience with satellites, robots, or other ...

Muon Space

Software Engineer, Entry-Level

San Jose, CA · On-site

$142K - $169K/yr

... Entry-level software engineers are expected to bring significant skills and training, and then to ... GPU programming or other relevant disciplines * Experience with satellites, robots, or other ...

Muon Space

Software Engineer, Entry-Level

San Jose, CA · On-site

$142K - $169K/yr

... Entry-level software engineers are expected to bring significant skills and training, and then to ... GPU programming or other relevant disciplines * Experience with satellites, robots, or other ...

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Gpu Entry Level information

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$25K

$47.8K

$68.5K

How much do gpu entry level jobs pay per year?

As of Aug 21, 2026, the average yearly pay for gpu entry level in the United States is $47,831.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,500.00 and $52,000.00 per year, depending on experience, location, and employer.

What is a GPU entry level?

GPU entry-level jobs are positions designed for individuals who are new to working with graphics processing units (GPUs) and related technologies. These roles typically involve assisting in the development, testing, or optimization of GPU hardware or software, and may include tasks such as programming, debugging, or supporting graphics applications. Candidates often have a background in computer science, electrical engineering, or a related field, but may not require extensive professional experience. Entry-level GPU jobs are a great way to gain hands-on experience and build skills in areas like parallel computing, 3D graphics, and machine learning using GPUs.

What are the key skills and qualifications needed to thrive as an entry-level GPU engineer?

To thrive as an Entry-Level GPU Engineer, you typically need a solid background in computer science or electrical engineering, with knowledge of graphics programming languages such as CUDA or OpenCL. Familiarity with GPU architectures, hardware debugging tools, and version control systems like Git is often required. Strong problem-solving skills, attention to detail, and the ability to work collaboratively are important soft skills in this role. These competencies ensure effective development and optimization of GPU solutions, contributing to the performance and reliability of graphics and computing applications.

What are some typical challenges faced by entry-level GPU engineers, and how can they overcome them?

Entry-level GPU engineers often encounter challenges such as getting familiar with complex hardware architectures, optimizing code for parallel processing, and debugging performance issues. To overcome these, it's helpful to actively seek mentorship, participate in code reviews, and use profiling tools to analyze performance bottlenecks. Collaborating with more experienced team members and staying updated with the latest GPU development practices can significantly ease the learning curve and foster professional growth.

What is the difference between Gpu Entry Level vs Gpu Technician?

AspectGpu Entry LevelGpu Technician
Required CredentialsHigh school diploma or equivalent; basic understanding of GPU hardwareAssociate degree or certification in computer hardware or electronics; technical training
Work EnvironmentEntry-level positions, often in retail or support rolesTechnical repair shops, data centers, or manufacturing facilities
Industry UsageCustomer support, basic troubleshootingHardware diagnostics, repairs, and maintenance

The main difference is that Gpu Entry Level roles focus on basic support and customer service, while Gpu Technicians perform hands-on hardware repairs and diagnostics. Gpu Technicians typically require more technical training and certifications, working in specialized environments. Both roles are essential in the GPU industry but differ in complexity and responsibilities.

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What states have the most Gpu Entry Level jobs?

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Gpu Entry Level jobs near you
Infographic showing various Gpu Entry Level job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 80% In-person, and 20% Hybrid job distribution, with an average salary of $47,831 per year, or $23 per hour.

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

Hudson Manpower

Waukesha, WI • On-site

Contractor

Re-posted 17 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
Only USC / GC
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: prasad@hudsonmanpower.com

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