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Gpu Programmer Jobs (NOW HIRING)

Sciforium

GPU Kernel Engineer

San Francisco, CA · On-site

$190K - $250K/yr

About the role We are seeking a highly skilled GPU Kernel Engineer who is passionate about pushing the limits of performance on modern accelerators. In this role, you will design and optimize custom ...

Google

Software Engineer, GPU Performance

Sunnyvale, CA · On-site

$163K/yr

Google is seeking a Software Engineer specializing in GPU Performance to develop next-generation technologies that enhance how users interact with information. The role involves building ...

Qualcomm

GPU Systems Driver Engineer

San Diego, CA · On-site

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: GPU System Driver Team are looking for talented software engineers to develop in-house GPU drivers to verify GPU function ...

ConfigUSA

CUDA Programmer

Waukesha, WI · On-site

Profile and tune GPU applications for performance, memory efficiency, and scalability. * Work with CPU-GPU parallel programming models and optimize data transfer. * Leverage NVIDIA libraries (CUDA ...

Qualcomm

GPU Compiler Engineer

San Diego, CA · On-site

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation ...

Qualcomm

GPU Compiler Engineer

San Diego, CA · On-site

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation ...

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How much do gpu programmer jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for gpu programmer in the United States is $39.54, according to ZipRecruiter salary data. Most workers in this role earn between $25.72 and $51.44 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Gpu Programmer position, and why are they important?

To thrive as a GPU Programmer, you need a solid background in computer science, experience with parallel computing concepts, and proficiency in GPU programming languages like CUDA or OpenCL. Familiarity with development tools such as NVIDIA Nsight, profiling utilities, and version control systems is typically required, while relevant certifications in GPU computing can be beneficial. Strong problem-solving ability, collaboration skills, and attention to detail help differentiate top performers in this field. These skills are essential for optimizing code performance, successfully working in dynamic teams, and meeting the high computational demands of modern applications.

What are the typical daily responsibilities of a GPU Programmer?

As a GPU Programmer, your daily tasks often involve designing, developing, and optimizing algorithms that leverage GPU architectures for increased performance in applications such as graphics rendering, scientific computing, or machine learning. You will routinely write and debug parallel code, profile workloads to find bottlenecks, and collaborate with software engineers, data scientists, and hardware specialists to integrate GPU-accelerated solutions. Documentation and code reviews are also important parts of your routine to ensure maintainability and knowledge sharing within the team. This role typically combines independent project work with regular cross-disciplinary collaboration, making adaptability and teamwork key to success.

What does a GPU Programmer do?

A GPU Programmer specializes in writing and optimizing code that runs on Graphics Processing Units (GPUs). They use parallel computing techniques and languages like CUDA or OpenCL to accelerate tasks such as graphics rendering, scientific simulations, and machine learning. Their work involves optimizing performance, managing memory efficiently, and ensuring compatibility across different hardware architectures.

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Gpu Programmer jobs near you
Infographic showing various Gpu Programmer job openings in the United States as of May 2026, with employment types broken down into 6% Internship, 76% Full Time, and 18% Contract. Highlights an 76% In-person, and 24% Remote job distribution, with an average salary of $82,234 per year, or $39.5 per hour.

Systems Research Engineer, GPU Programming

Together AI

San Francisco, CA • On-site, Remote

$160K - $230K/yr

Other

Medical

Posted 17 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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