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Gpu Programming Jobs (NOW HIRING)

Anthropic

Performance Engineer, GPU

San Francisco, CA · On-site

$280K - $850K/yr

Have deep experience with GPU programming and optimization at scale * Are impact-driven, passionate about delivering measurable performance breakthroughs * Can navigate complex systems from hardware ...

Weekday AI

CUDA Engineering Expert

$80 - $100/hr

This opportunity is designed for freelancers with strong C++ skills, practical GPU programming experience, and the ability to improve kernel performance using profiler-guided analysis. You'll help ...

Nvidia

Senior Compiler Engineer - Rust GPU

Seattle, WA

$139K - $183K/yr

Deep expertise in the Rust programming language, including a strong grasp of compiler internals ... Solid understanding of parallel programming models, GPU architectures, and CUDA programming.

Qualcomm

Senior GPU SW Engineer

San Diego, CA · On-site

$148K - $183K/yr

Extensive programming knowledge in C/C++ * Strong knowledge of GPU hardware and graphics concepts * Demonstrated ability to deliver software features and products while ensuring the highest standards ...

Nvidia

OR

Strong programming skills in Python and C++! * Hands-on experience with PyTorch or a similar tensor/autograd framework. * Experience optimizing GPU-accelerated workloads using CUDA, C++/CUDA ...

Nvidia

Senior Compiler Engineer - Rust GPU

Austin, TX

$121K - $160K/yr

Deep expertise in the Rust programming language, including a strong grasp of compiler internals ... Solid understanding of parallel programming models, GPU architectures, and CUDA programming.

Qualcomm

Senior GPU SW Engineer

San Diego, CA · On-site

$116K - $175K/yr

Extensive programming knowledge in C/C++ * Strong knowledge of GPU hardware and graphics concepts * Demonstrated ability to deliver software features and products while ensuring the highest standards ...

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Gpu Programming information

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How much do gpu programming jobs pay per year?

As of Aug 11, 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 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.

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.

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Gpu Programming jobs near you
Infographic showing various Gpu Programming job openings in the United States as of August 2026, with employment types broken down into 5% Internship, 85% Full Time, and 10% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $64,974 per year, or $31.2 per hour.

System Software Engineer -- GPU & Accelerated Compute

Sunday

Redwood City, CA • On-site

$211K - $251K/yr

Full-time

Re-posted 12 days ago

Job description

Job Summary:
Sunday is developing personal robots to reclaim the hours lost to repetitive tasks, aiming to make generalized robots broadly accessible. They are seeking a System Software Engineer focused on GPU and accelerated compute to own the accelerated compute layer of their ML & Robotics Infra, ensuring efficient model execution and GPU scheduling for real-time robotic systems.
Responsibilities:
• You’ll own and contribute to the accelerated compute layer of the ML & Robotics Infra, including:
• Efficient model execution and switching: Reduce gpu kernel launch overheads and make swapping between models on the same device fast and predictable
• GPU scheduling and time-slicing: Arbitrate GPU access across concurrent users (model inference, SLAM, and other robotics applications) with predictable latency
• Camera pipeline: Drive low-latency transfer of camera frames into GPU memory, integrating with HW accelerate encode/decode (NVDEC/NVENC) where appropriate
• CPU ↔ GPU data transfer: Build efficient, low-overhead data movement between host and device, including pinned memory, zero-copy paths, and asynchronous transfer patterns
• CPU/GPU synchronization: Design synchronization primitives and patterns that minimize stalls and keep inference pipelines full
Qualifications:
Required:
• 2+ years of experience developing gpu systems software
• Strong proficiency in CUDA and a systems language such as C++, C, or Rust
• Solid understanding of GPU architecture, GPU workloads, and the tradeoffs involved in time-slicing and sharing the device across users
• Hands-on experience with the CUDA ecosystem: CUDA runtime API, CUDA Graphs, and CUDA IPC
• Familiarity with GPU sharing mechanisms such as MPS and MIG
• Experience with GPU profiling tools such as Nsight Systems and Nsight Compute
• Solid Linux fundamentals: scheduling, IPC, memory management, and performance tuning
Preferred:
• Contributions to CUDA libraries or other GPU programming libraries
• Experience with camera pipeline integration and NVDEC/NVENC
• Experience optimizing model inference on embedded GPU platforms (e.g., Jetson)
• Experience with observability and tracing for GPU-accelerated workloads
Company:
Sunday is a robotics and artificial intelligence company that develops an autonomous home robot to assist with household tasks. Founded in 2024, the company is headquartered in Mountain View, USA, with a team of 51-200 employees. The company is currently Early Stage.

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