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Full Time Gpu Programming Jobs (NOW HIRING)

Qualcomm

Technical Program Manager - GPU AI

San Diego, CA · On-site

$171K - $256K/yr

This role is based in San Diego, CA and requires full-time onsite work (5 days per week). What You Will Be Doing * Lead program management for GPU AI activities across GPU engineering teams. * Drive ...

Waymo

Software Engineer, GPU

Mountain View, CA · On-site

$204K - $259K/yr

Proven expertise in C++ programming * Bachelor degrees in EECS, coupled with a minimum of three ... full-time position across US locations is listed below. Actual starting pay will be based on job ...

Rutgers University

Research Programmer

Piscataway, NJ · On-site

$120K - $130K/yr

... Status Full Time Posting Number 25FA0745 Posting Open Date 08/01/2025 Posting Close Date ... Experience with GPU programming and optimization for ML models, utilizing frameworks, like CUDA or ...

Booz Allen Hamilton

AI/ML Engineer, Mid

Dayton, OH · On-site

$77K - $176K/yr

Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of applications and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

AI/ML Engineer, Mid

Dayton, OH · On-site

$77K - $176K/yr

Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of applications and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton

AI/ML Engineer, Mid

Dayton, OH · On-site

$77K - $176K/yr

Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of applications and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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Full Time Gpu Programming information

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How much do full time gpu programming jobs pay per year?

As of Jul 10, 2026, the average yearly pay for full time gpu programming in the United States is $64,974.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,500.00 and $80,000.00 per year, depending on experience, location, and employer.

What are some typical challenges faced by professionals in full-time GPU programming roles, and how can they be addressed?

Full-time GPU programmers often encounter challenges such as optimizing code for parallel execution, managing memory efficiently, and debugging complex kernels. These tasks require a deep understanding of GPU architecture and tools like CUDA or OpenCL. Collaborating closely with other developers, data scientists, and hardware engineers is essential to identify performance bottlenecks and ensure that solutions meet project requirements. Staying updated with the latest advancements and regularly profiling code can help address these challenges effectively.

What are the key skills and qualifications needed to thrive as a Full Time GPU Programmer, and why are they important?

To thrive as a Full Time GPU Programmer, you need strong programming skills in languages like C++ and Python, a deep understanding of parallel computing, and often a degree in computer science or a related field. Familiarity with GPU programming frameworks such as CUDA or OpenCL, and experience with performance profiling tools, are typically required. Problem-solving ability, attention to detail, and effective teamwork distinguish top performers in this role. These skills ensure efficient development of high-performance, scalable applications that leverage GPU capabilities for computational tasks.

What is the difference between Full Time Gpu Programming vs Gpu Software Engineer?

AspectFull Time Gpu ProgrammingGpu Software Engineer
Required CredentialsBachelor's or higher in Computer Science, Engineering, or related field; experience with GPU programming languagesSimilar credentials; often requires experience with CUDA, OpenCL, or Vulkan
Work EnvironmentPrimarily focused on developing and optimizing GPU code, often in research or high-performance computing settingsDesigning, developing, and maintaining GPU-based software applications in industry or research
Employer & Industry UsageTech companies, research labs, gaming, and scientific computingTech firms, gaming, AI, and scientific industries

Both roles involve GPU programming skills, but Full Time Gpu Programming emphasizes writing and optimizing GPU code, while Gpu Software Engineer focuses on developing complete GPU-accelerated software solutions. The roles often overlap but differ in scope and application.

What is a Full Time GPU Programmer?

A Full Time GPU Programmer is a software developer who specializes in writing and optimizing code to run on Graphics Processing Units (GPUs). These professionals use languages like CUDA or OpenCL to leverage the parallel processing capabilities of GPUs for tasks such as scientific computing, machine learning, graphics rendering, and more. They work on designing, implementing, and debugging GPU-accelerated algorithms to improve performance and efficiency in various applications. Full Time GPU Programmers often collaborate with other engineers and researchers to integrate GPU solutions into larger software systems.
More about Full Time Gpu Programming jobs
What are the most commonly searched types of Gpu Programming jobs? The most popular types of Gpu Programming jobs are:
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What job categories do people searching Full Time Gpu Programming jobs look for? The top searched job categories for Full Time Gpu Programming jobs are:
Full Time Gpu Programming jobs near you
Infographic showing various Full Time Gpu Programming job openings in the United States as of July 2026, with employment types broken down into 74% Full Time, 24% Part Time, and 2% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $64,974 per year, or $31.2 per hour.
Systems Research Engineer, GPU Programming

Systems Research Engineer, GPU Programming

Together AI

San Francisco, CA • On-site

$160K - $230K/yr

Full-time

Medical

Re-posted 18 days ago

Job description

About the Role
As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.
Requirements
  • Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.
  • Knowledge of ML/AI applications and models
  • Knowledge of performance profiling and optimization tools for GPU programming
  • Excellent problem-solving and analytical skills
  • Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences
Responsibilities
  • Optimize and fine-tune GPU code to achieve better performance and scalability
  • Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
  • Stay up-to-date with the latest advancements in GPU programming techniques and technologies
About Together AI
Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.
Compensation
We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
Equal Opportunity
Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
Please see our privacy policy at https://www.together.ai/privacy

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