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Cuda Developer Jobs (NOW HIRING)

Nvidia

System Software Engineer - CUDA Chips

Santa Clara, CA · On-site

$203K - $240K/yr

We are hiring engineers to work on the CUDA driver, a core component of our platform for accelerating general purpose computation on the GPU. Our team delivers features and improvements to better ...

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How much do cuda developer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for cuda developer in the United States is $111,845.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $130,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Cuda Developers in their daily work?

Cuda Developers often encounter challenges related to optimizing code for maximum performance while managing the unique memory hierarchies and parallel processing features of GPU architectures. Debugging and profiling GPU code can be more complex than standard CPU programming, requiring specialized tools and a strong understanding of concurrency. Collaboration with data scientists, machine learning engineers, and software architects is common, as Cuda Developers often integrate their code into larger, multi-disciplinary projects. These challenges make the role both stimulating and rewarding for those who enjoy solving intricate computational problems.

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

To thrive as a Cuda Developer, you need strong proficiency in C/C++ programming, parallel computing concepts, and hands-on experience with NVIDIA CUDA architecture. Familiarity with GPU development tools such as NVIDIA Nsight, CUDA Toolkit, and relevant certifications can further validate your expertise. Problem-solving skills, attention to detail, and effective collaboration are valuable soft skills in this position. These capabilities are crucial for efficiently developing, debugging, and optimizing high-performance GPU-accelerated applications in demanding computational environments.

What is a Cuda Developer job?

A CUDA Developer is a software engineer who specializes in programming using NVIDIA's CUDA (Compute Unified Device Architecture) platform. They leverage parallel computing to optimize and accelerate applications, mainly in fields like AI, scientific computing, and high-performance computing. Their responsibilities often include writing GPU-accelerated code, optimizing performance, and working with frameworks like TensorFlow or PyTorch.

More about CUDA Developer jobs
What cities are hiring for Cuda Developer jobs? Cities with the most Cuda Developer job openings:
What are the most commonly searched types of Cuda Developer jobs? The most popular types of Cuda Developer jobs are:
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CUDA Developer jobs near you
Infographic showing various Cuda Developer job openings in the United States as of July 2026, with employment types broken down into 84% Full Time, 1% Part Time, 12% Temporary, 1% Contract, and 2% Nights. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $111,845 per year, or $53.8 per hour.

Technical Marketing Engineer -- CUDA-Q Developer Enablement

NVIDIA AI

Santa Clara, CA • On-site

Full-time

Posted 14 days ago

Job description

Job Summary:
NVIDIA AI is building the leading platform for Quantum Computing with CUDA-Q, and they are seeking a Technical Marketing Engineer to drive technical enablement across a broad developer ecosystem. The role involves creating content, tools, and experiences to help quantum researchers, HPC practitioners, and AI developers effectively use CUDA-Q.
Responsibilities:
• Analyze developer journey needs with product teams and domain experts to identify and close gaps for both human and agent workflows using CUDA-Q
• Define practical standards for developer surfaces including GitHub, docs, example code, and onboarding that work for both developers and the AI agents they use
• Create MCP servers, Agent Skills, API documentation patterns, agent-consumable tests, and prompt-ready templates
• Build and maintain enablement resources — templates, runbooks, checklists, context files, and reference implementations — that quantum researchers and developers can use directly
• Evaluate content performance using human engagement metrics and agent signals to continuously improve developer time-to-value with CUDA-Q
• Define success criteria and evaluation frameworks for agentic developer tools — designing benchmarks, running evals, and translating results into actionable product improvements
• Track emerging AX, GEO, and AI citation research and translate findings into practical guidance for teams building quantum computing applications
Qualifications:
Required:
• Bachelor's degree in a technical field, or equivalent experience
• 5+ years work of related work experience
• Experience with documentation systems, information architecture, and content strategy for developer-facing and agent-facing technical content
• Understanding of agent-consumable content standards such as llms.txt, MCP, Agent Skills, and API documentation patterns
• Knowledge of quantum computing concepts and familiarity with CUDA-Q or similar quantum computing frameworks
• Proficiency with agentic coding harnesses such as Claude Code or Codex, and the judgment to evaluate AX tooling — from MCP servers and Agent Skills to API docs and prompt templates — for different contexts
• Strong communication and interpersonal skills, with the ability to collaborate effectively with researchers, engineers, and product teams
• Experience designing evaluations for developer or ML products — controlled experiments, human eval pipelines, or benchmark harnesses — with clear success criteria defined upfront
• A track record of staying ahead of fast paced technology shifts and translating findings into practical guidance before it becomes conventional wisdom
Preferred:
• Hands-on experience with CUDA-Q or other quantum computing frameworks, and an intuition for how quantum workloads connect to the broader GPU-accelerated computing stack
• Track record of building enablement resources — libraries, playbooks, templates — that developer teams actually use, and driving adoption across organizations
• Contributions to open-source quantum computing, AI, or developer tooling projects
• Experience using data and analytics to measure developer onboarding, identify friction points, and drive improvements
Company:
Explore the latest breakthroughs made possible with AI. Founded in , the company is headquartered in Santa Clara, CA, US, , with a team of 10001+ employees. The company is currently Late Stage.

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