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Gpu Programming Jobs (NOW HIRING)

YO AI Labs

GPU Programmer - Remote

Austin, TX · Remote

$60 - $85/hr

You will apply your expertise in GPU programming, performance optimization, and C++ development to build high-performance solutions. Key Responsibilities * Design, implement, and optimize GPU ...

YO AI Labs

GPU Programmer - Remote

Seattle, WA · Remote

$60 - $85/hr

You will apply your expertise in GPU programming, performance optimization, and C++ development to build high-performance solutions. Key Responsibilities * Design, implement, and optimize GPU ...

YO AI Labs

GPU Programmer - Remote

Seattle, WA · Remote

$60 - $85/hr

You will apply your expertise in GPU programming, performance optimization, and C++ development to build high-performance solutions. Key Responsibilities * Design, implement, and optimize GPU ...

YO AI Labs

GPU Programmer - Remote

Chicago, IL · Remote

$60 - $85/hr

You will apply your expertise in GPU programming, performance optimization, and C++ development to build high-performance solutions. Key Responsibilities * Design, implement, and optimize GPU ...

YO AI Labs

GPU Programmer - Remote

Miami, FL · Remote

$60 - $85/hr

You will apply your expertise in GPU programming, performance optimization, and C++ development to build high-performance solutions. Key Responsibilities * Design, implement, and optimize GPU ...

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How much do gpu programming jobs pay per year?

As of Sep 15, 2026, the average yearly pay for 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 is GPU programming?

A GPU Programming job involves writing and optimizing code to run on Graphics Processing Units (GPUs) for parallel computing tasks. This role is commonly found in fields like machine learning, scientific computing, gaming, and data analytics. GPU programmers use languages such as CUDA, OpenCL, or Vulkan to accelerate computations and improve performance. They work closely with software engineers and data scientists to optimize algorithms for high-performance applications.

What types of projects or applications do GPU programmers commonly work on?

GPU Programmers are often involved in developing or optimizing software for high-performance applications such as machine learning, scientific simulations, real-time rendering in gaming and visualization, and video/image processing tools. Their daily work may include collaborating with software engineers, data scientists, and hardware teams to create efficient, scalable parallel algorithms that leverage GPU capabilities. The role frequently requires problem-solving to maximize computational efficiency and troubleshooting complex performance bottlenecks. By working across multidisciplinary teams, GPU Programmers help deliver robust solutions for data-intensive problems in areas like healthcare, finance, automotive technology, and entertainment.

What are the key skills and qualifications needed to thrive in GPU programming, and why are they important?

To excel in GPU Programming, you need a strong background in parallel computing concepts, mathematics, and proficiency in languages such as CUDA, OpenCL, or DirectX/OpenGL, often supported by a degree in computer science, engineering, or a related field. Familiarity with NVIDIA and AMD GPU development tools, performance profilers, and possibly certifications like NVIDIA's Deep Learning Institute courses are valuable. Teamwork, effective communication, and strong problem-solving abilities are essential soft skills in this field. These competencies enable efficient development, optimization, and integration of high-performance GPU code in real-world applications.

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GPU Programming jobs near you
Infographic showing various Gpu Programming job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $64,974 per year, or $31.2 per hour.

Systems Research Engineer, GPU Programming

San Francisco, CA • On-site, Remote

Together AI
Internet and IT • 51 - 200 employees
Learn more about Together AIexternal

$200K - $300K/yr

Full-time

Medical

Re-posted 25 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, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

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: $200,000 - $300,000 + 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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