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Cuda Programming Jobs (NOW HIRING)

Genmo

GPU Performance Engineer

San Francisco, CA · On-site

Strong CUDA programming skills with production kernel development * Deep understanding of GPU architecture (memory hierarchy, SMs, warps) * Track record of achieving significant performance ...

Genmo

GPU Performance Engineer

San Francisco, CA · On-site

Strong CUDA programming skills with production kernel development * Deep understanding of GPU architecture (memory hierarchy, SMs, warps) * Track record of achieving significant performance ...

Nvidia

NVIDIA is seeking a Senior Technical Marketing Engineer (TME) to share the CUDA platform with our developer community. TMEs are drawn from outstanding software engineers and scientists who enjoy ...

Figure

Helix AI Engineer, Perception

San Jose, CA · On-site

Preferred : • Experience with CUDA programming and real-time systems performance optimization. • Familiarity with scalable data engineering toolchains like Spark and Ray. • Strong publication ...

Nvidia

Senior Compiler Engineer - PVA

Santa Clara, CA · Hybrid

$122K - $168K/yr

NVIDIA has revolutionized parallel computing, and the development of the CUDA programming model has fueled its power. NVIDIA developed a powerful computing platform (PVA) focused on vision and deep ...

Raytheon

Software Engineer II -Algorithms (Onsite)

Plano, TX · On-site

$93K - $128K/yr

... CUDA programming for Nvidia accelerators. • Experience with MATLAB, Python, and other analysis tools. • Active and transferable Top Secret U.S. government issued security clearance. Company

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How much do cuda programming jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for cuda programming in the United States is $54.36, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $63.46 per hour, depending on experience, location, and employer.

What is the salary of NVIDIA CUDA developer?

The salary of an NVIDIA CUDA developer typically ranges from $80,000 to $130,000 annually, depending on experience, location, and industry. Skilled CUDA programmers with advanced knowledge of parallel computing and GPU architecture tend to earn higher salaries.

What jobs use CUDA?

Jobs that use CUDA include roles such as GPU programmer, software developer, data scientist, and machine learning engineer, especially in fields like high-performance computing, artificial intelligence, and scientific research. These roles often require knowledge of parallel programming, C++, and GPU architecture, and involve developing or optimizing software to run efficiently on NVIDIA GPUs.

Are CUDA programmers in demand?

CUDA programmers are in high demand due to the growing use of GPU computing in fields like artificial intelligence, scientific research, and data processing. Skills in parallel programming, GPU architecture, and CUDA toolkit are highly valued, and job opportunities are expected to increase as these technologies expand across industries.

How much do CUDA engineers make?

CUDA engineers typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in parallel programming and GPU optimization can command higher salaries, especially in tech hubs or companies with advanced AI and high-performance computing needs.

What is the difference between Cuda Programming vs GPU Developer?

AspectCuda ProgrammingGPU Developer
Required CredentialsKnowledge of CUDA, C/C++, parallel computingKnowledge of GPU architecture, CUDA, OpenCL, C/C++
Work EnvironmentHigh-performance computing, scientific research, AIGraphics, gaming, scientific visualization, AI
Industry UsageTech companies, research labs, AI firmsGaming, entertainment, tech, research

While Cuda Programming focuses specifically on writing code using NVIDIA's CUDA platform for parallel processing, GPU Developers have a broader role that includes designing, optimizing, and implementing GPU-based solutions across various platforms and technologies. Both roles require knowledge of GPU architecture and programming languages like C/C++, but GPU Developers often work on a wider range of applications beyond CUDA-specific projects.

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What job categories do people searching Cuda Programming jobs look for? The top searched job categories for Cuda Programming jobs are:
Cuda Programming jobs near you
Infographic showing various Cuda Programming job openings in the United States as of July 2026, with employment types broken down into 12% As Needed, 44% Full Time, 24% Temporary, 18% Nights, and 2% Summer. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $113,061 per year, or $54.4 per hour.
Staff Software Engineer, ML Acceleration

Staff Software Engineer, ML Acceleration

Stack AV

Pittsburgh, PA • On-site

Full-time

Posted 10 days ago

Job description

Job Summary:
Stack AV is developing revolutionary AI and advanced autonomous systems aimed at enhancing safety and efficiency in the trucking transportation industry. The Staff Software Engineer, ML Acceleration will focus on increasing product development velocity by optimizing machine learning iterations and promoting best practices among Machine Learning Engineers across the company.
Responsibilities:
• Analyze ML models to identify and resolve performance bottlenecks.
• Incorporate OSS tools to enable ML engineers self-sufficiently profile and optimize models.
• Deliver solutions to streamline model deployment across various hardware platforms.
• Collaborate with ML researchers to balance model accuracy and speed.
• Implement optimizations using CUDA, Triton, and custom kernels.
• Promote Engineering Excellence: Maintain a high bar for engineering excellence in their own work but also set a culture of engineering excellence within the team.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 5+ years of experience (including experience with GPU programming and optimization)
• Strong programming skills in C++ and Python
• Proven experience in GPU programming and optimization
• Familiarity with deep learning frameworks, especially PyTorch
• CUDA programming
• Triton language for GPU kernels
• PyTorch optimization techniques
• TensorRT implementation
• ONNX model conversion and deployment
• Custom GPU kernel development
• Deep understanding of GPU architectures and performance optimization
• Strong analytical and problem-solving skills
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders
Preferred:
• Autonomous vehicles (AV) experience is a bonus
Company:
Stack AV operates in the transportation industry that develops advanced autonomous systems. Founded in 2023, the company is headquartered in Pittsburgh, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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